1 2 /* 3 Defines the basic matrix operations for the BAIJ (compressed row) 4 matrix storage format. 5 */ 6 #include <../src/mat/impls/baij/seq/baij.h> /*I "petscmat.h" I*/ 7 #include <petscblaslapack.h> 8 #include <petsc-private/kernels/blockinvert.h> 9 #include <petsc-private/kernels/blockmatmult.h> 10 11 #undef __FUNCT__ 12 #define __FUNCT__ "MatInvertBlockDiagonal_SeqBAIJ" 13 PetscErrorCode MatInvertBlockDiagonal_SeqBAIJ(Mat A,const PetscScalar **values) 14 { 15 Mat_SeqBAIJ *a = (Mat_SeqBAIJ*) A->data; 16 PetscErrorCode ierr; 17 PetscInt *diag_offset,i,bs = A->rmap->bs,mbs = a->mbs,ipvt[5],bs2 = bs*bs,*v_pivots; 18 MatScalar *v = a->a,*odiag,*diag,*mdiag,work[25],*v_work; 19 PetscReal shift = 0.0; 20 21 PetscFunctionBegin; 22 if (a->idiagvalid) { 23 if (values) *values = a->idiag; 24 PetscFunctionReturn(0); 25 } 26 ierr = MatMarkDiagonal_SeqBAIJ(A);CHKERRQ(ierr); 27 diag_offset = a->diag; 28 if (!a->idiag) { 29 ierr = PetscMalloc1(2*bs2*mbs,&a->idiag);CHKERRQ(ierr); 30 ierr = PetscLogObjectMemory((PetscObject)A,2*bs2*mbs*sizeof(PetscScalar));CHKERRQ(ierr); 31 } 32 diag = a->idiag; 33 mdiag = a->idiag+bs2*mbs; 34 if (values) *values = a->idiag; 35 /* factor and invert each block */ 36 switch (bs) { 37 case 1: 38 for (i=0; i<mbs; i++) { 39 odiag = v + 1*diag_offset[i]; 40 diag[0] = odiag[0]; 41 mdiag[0] = odiag[0]; 42 diag[0] = (PetscScalar)1.0 / (diag[0] + shift); 43 diag += 1; 44 mdiag += 1; 45 } 46 break; 47 case 2: 48 for (i=0; i<mbs; i++) { 49 odiag = v + 4*diag_offset[i]; 50 diag[0] = odiag[0]; diag[1] = odiag[1]; diag[2] = odiag[2]; diag[3] = odiag[3]; 51 mdiag[0] = odiag[0]; mdiag[1] = odiag[1]; mdiag[2] = odiag[2]; mdiag[3] = odiag[3]; 52 ierr = PetscKernel_A_gets_inverse_A_2(diag,shift);CHKERRQ(ierr); 53 diag += 4; 54 mdiag += 4; 55 } 56 break; 57 case 3: 58 for (i=0; i<mbs; i++) { 59 odiag = v + 9*diag_offset[i]; 60 diag[0] = odiag[0]; diag[1] = odiag[1]; diag[2] = odiag[2]; diag[3] = odiag[3]; 61 diag[4] = odiag[4]; diag[5] = odiag[5]; diag[6] = odiag[6]; diag[7] = odiag[7]; 62 diag[8] = odiag[8]; 63 mdiag[0] = odiag[0]; mdiag[1] = odiag[1]; mdiag[2] = odiag[2]; mdiag[3] = odiag[3]; 64 mdiag[4] = odiag[4]; mdiag[5] = odiag[5]; mdiag[6] = odiag[6]; mdiag[7] = odiag[7]; 65 mdiag[8] = odiag[8]; 66 ierr = PetscKernel_A_gets_inverse_A_3(diag,shift);CHKERRQ(ierr); 67 diag += 9; 68 mdiag += 9; 69 } 70 break; 71 case 4: 72 for (i=0; i<mbs; i++) { 73 odiag = v + 16*diag_offset[i]; 74 ierr = PetscMemcpy(diag,odiag,16*sizeof(PetscScalar));CHKERRQ(ierr); 75 ierr = PetscMemcpy(mdiag,odiag,16*sizeof(PetscScalar));CHKERRQ(ierr); 76 ierr = PetscKernel_A_gets_inverse_A_4(diag,shift);CHKERRQ(ierr); 77 diag += 16; 78 mdiag += 16; 79 } 80 break; 81 case 5: 82 for (i=0; i<mbs; i++) { 83 odiag = v + 25*diag_offset[i]; 84 ierr = PetscMemcpy(diag,odiag,25*sizeof(PetscScalar));CHKERRQ(ierr); 85 ierr = PetscMemcpy(mdiag,odiag,25*sizeof(PetscScalar));CHKERRQ(ierr); 86 ierr = PetscKernel_A_gets_inverse_A_5(diag,ipvt,work,shift);CHKERRQ(ierr); 87 diag += 25; 88 mdiag += 25; 89 } 90 break; 91 case 6: 92 for (i=0; i<mbs; i++) { 93 odiag = v + 36*diag_offset[i]; 94 ierr = PetscMemcpy(diag,odiag,36*sizeof(PetscScalar));CHKERRQ(ierr); 95 ierr = PetscMemcpy(mdiag,odiag,36*sizeof(PetscScalar));CHKERRQ(ierr); 96 ierr = PetscKernel_A_gets_inverse_A_6(diag,shift);CHKERRQ(ierr); 97 diag += 36; 98 mdiag += 36; 99 } 100 break; 101 case 7: 102 for (i=0; i<mbs; i++) { 103 odiag = v + 49*diag_offset[i]; 104 ierr = PetscMemcpy(diag,odiag,49*sizeof(PetscScalar));CHKERRQ(ierr); 105 ierr = PetscMemcpy(mdiag,odiag,49*sizeof(PetscScalar));CHKERRQ(ierr); 106 ierr = PetscKernel_A_gets_inverse_A_7(diag,shift);CHKERRQ(ierr); 107 diag += 49; 108 mdiag += 49; 109 } 110 break; 111 default: 112 ierr = PetscMalloc2(bs,&v_work,bs,&v_pivots);CHKERRQ(ierr); 113 for (i=0; i<mbs; i++) { 114 odiag = v + bs2*diag_offset[i]; 115 ierr = PetscMemcpy(diag,odiag,bs2*sizeof(PetscScalar));CHKERRQ(ierr); 116 ierr = PetscMemcpy(mdiag,odiag,bs2*sizeof(PetscScalar));CHKERRQ(ierr); 117 ierr = PetscKernel_A_gets_inverse_A(bs,diag,v_pivots,v_work);CHKERRQ(ierr); 118 diag += bs2; 119 mdiag += bs2; 120 } 121 ierr = PetscFree2(v_work,v_pivots);CHKERRQ(ierr); 122 } 123 a->idiagvalid = PETSC_TRUE; 124 PetscFunctionReturn(0); 125 } 126 127 #undef __FUNCT__ 128 #define __FUNCT__ "MatSOR_SeqBAIJ" 129 PetscErrorCode MatSOR_SeqBAIJ(Mat A,Vec bb,PetscReal omega,MatSORType flag,PetscReal fshift,PetscInt its,PetscInt lits,Vec xx) 130 { 131 Mat_SeqBAIJ *a = (Mat_SeqBAIJ*)A->data; 132 PetscScalar *x,*work,*w,*workt,*t; 133 const MatScalar *v,*aa = a->a, *idiag; 134 const PetscScalar *b,*xb; 135 PetscScalar s[7], xw[7]={0}; /* avoid some compilers thinking xw is uninitialized */ 136 PetscErrorCode ierr; 137 PetscInt m = a->mbs,i,i2,nz,bs = A->rmap->bs,bs2 = bs*bs,k,j,idx,it; 138 const PetscInt *diag,*ai = a->i,*aj = a->j,*vi; 139 140 PetscFunctionBegin; 141 its = its*lits; 142 if (flag & SOR_EISENSTAT) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"No support yet for Eisenstat"); 143 if (its <= 0) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONG,"Relaxation requires global its %D and local its %D both positive",its,lits); 144 if (fshift) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"Sorry, no support for diagonal shift"); 145 if (omega != 1.0) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"Sorry, no support for non-trivial relaxation factor"); 146 if ((flag & SOR_APPLY_UPPER) || (flag & SOR_APPLY_LOWER)) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"Sorry, no support for applying upper or lower triangular parts"); 147 148 if (!a->idiagvalid) {ierr = MatInvertBlockDiagonal(A,NULL);CHKERRQ(ierr);} 149 150 if (!m) PetscFunctionReturn(0); 151 diag = a->diag; 152 idiag = a->idiag; 153 k = PetscMax(A->rmap->n,A->cmap->n); 154 if (!a->mult_work) { 155 ierr = PetscMalloc1((2*k+1),&a->mult_work);CHKERRQ(ierr); 156 } 157 work = a->mult_work; 158 t = work + k+1; 159 if (!a->sor_work) { 160 ierr = PetscMalloc1(bs,&a->sor_work);CHKERRQ(ierr); 161 } 162 w = a->sor_work; 163 164 ierr = VecGetArray(xx,&x);CHKERRQ(ierr); 165 ierr = VecGetArrayRead(bb,&b);CHKERRQ(ierr); 166 167 if (flag & SOR_ZERO_INITIAL_GUESS) { 168 if (flag & SOR_FORWARD_SWEEP || flag & SOR_LOCAL_FORWARD_SWEEP) { 169 switch (bs) { 170 case 1: 171 PetscKernel_v_gets_A_times_w_1(x,idiag,b); 172 t[0] = b[0]; 173 i2 = 1; 174 idiag += 1; 175 for (i=1; i<m; i++) { 176 v = aa + ai[i]; 177 vi = aj + ai[i]; 178 nz = diag[i] - ai[i]; 179 s[0] = b[i2]; 180 for (j=0; j<nz; j++) { 181 xw[0] = x[vi[j]]; 182 PetscKernel_v_gets_v_minus_A_times_w_1(s,(v+j),xw); 183 } 184 t[i2] = s[0]; 185 PetscKernel_v_gets_A_times_w_1(xw,idiag,s); 186 x[i2] = xw[0]; 187 idiag += 1; 188 i2 += 1; 189 } 190 break; 191 case 2: 192 PetscKernel_v_gets_A_times_w_2(x,idiag,b); 193 t[0] = b[0]; t[1] = b[1]; 194 i2 = 2; 195 idiag += 4; 196 for (i=1; i<m; i++) { 197 v = aa + 4*ai[i]; 198 vi = aj + ai[i]; 199 nz = diag[i] - ai[i]; 200 s[0] = b[i2]; s[1] = b[i2+1]; 201 for (j=0; j<nz; j++) { 202 idx = 2*vi[j]; 203 it = 4*j; 204 xw[0] = x[idx]; xw[1] = x[1+idx]; 205 PetscKernel_v_gets_v_minus_A_times_w_2(s,(v+it),xw); 206 } 207 t[i2] = s[0]; t[i2+1] = s[1]; 208 PetscKernel_v_gets_A_times_w_2(xw,idiag,s); 209 x[i2] = xw[0]; x[i2+1] = xw[1]; 210 idiag += 4; 211 i2 += 2; 212 } 213 break; 214 case 3: 215 PetscKernel_v_gets_A_times_w_3(x,idiag,b); 216 t[0] = b[0]; t[1] = b[1]; t[2] = b[2]; 217 i2 = 3; 218 idiag += 9; 219 for (i=1; i<m; i++) { 220 v = aa + 9*ai[i]; 221 vi = aj + ai[i]; 222 nz = diag[i] - ai[i]; 223 s[0] = b[i2]; s[1] = b[i2+1]; s[2] = b[i2+2]; 224 while (nz--) { 225 idx = 3*(*vi++); 226 xw[0] = x[idx]; xw[1] = x[1+idx]; xw[2] = x[2+idx]; 227 PetscKernel_v_gets_v_minus_A_times_w_3(s,v,xw); 228 v += 9; 229 } 230 t[i2] = s[0]; t[i2+1] = s[1]; t[i2+2] = s[2]; 231 PetscKernel_v_gets_A_times_w_3(xw,idiag,s); 232 x[i2] = xw[0]; x[i2+1] = xw[1]; x[i2+2] = xw[2]; 233 idiag += 9; 234 i2 += 3; 235 } 236 break; 237 case 4: 238 PetscKernel_v_gets_A_times_w_4(x,idiag,b); 239 t[0] = b[0]; t[1] = b[1]; t[2] = b[2]; t[3] = b[3]; 240 i2 = 4; 241 idiag += 16; 242 for (i=1; i<m; i++) { 243 v = aa + 16*ai[i]; 244 vi = aj + ai[i]; 245 nz = diag[i] - ai[i]; 246 s[0] = b[i2]; s[1] = b[i2+1]; s[2] = b[i2+2]; s[3] = b[i2+3]; 247 while (nz--) { 248 idx = 4*(*vi++); 249 xw[0] = x[idx]; xw[1] = x[1+idx]; xw[2] = x[2+idx]; xw[3] = x[3+idx]; 250 PetscKernel_v_gets_v_minus_A_times_w_4(s,v,xw); 251 v += 16; 252 } 253 t[i2] = s[0]; t[i2+1] = s[1]; t[i2+2] = s[2]; t[i2 + 3] = s[3]; 254 PetscKernel_v_gets_A_times_w_4(xw,idiag,s); 255 x[i2] = xw[0]; x[i2+1] = xw[1]; x[i2+2] = xw[2]; x[i2+3] = xw[3]; 256 idiag += 16; 257 i2 += 4; 258 } 259 break; 260 case 5: 261 PetscKernel_v_gets_A_times_w_5(x,idiag,b); 262 t[0] = b[0]; t[1] = b[1]; t[2] = b[2]; t[3] = b[3]; t[4] = b[4]; 263 i2 = 5; 264 idiag += 25; 265 for (i=1; i<m; i++) { 266 v = aa + 25*ai[i]; 267 vi = aj + ai[i]; 268 nz = diag[i] - ai[i]; 269 s[0] = b[i2]; s[1] = b[i2+1]; s[2] = b[i2+2]; s[3] = b[i2+3]; s[4] = b[i2+4]; 270 while (nz--) { 271 idx = 5*(*vi++); 272 xw[0] = x[idx]; xw[1] = x[1+idx]; xw[2] = x[2+idx]; xw[3] = x[3+idx]; xw[4] = x[4+idx]; 273 PetscKernel_v_gets_v_minus_A_times_w_5(s,v,xw); 274 v += 25; 275 } 276 t[i2] = s[0]; t[i2+1] = s[1]; t[i2+2] = s[2]; t[i2+3] = s[3]; t[i2+4] = s[4]; 277 PetscKernel_v_gets_A_times_w_5(xw,idiag,s); 278 x[i2] = xw[0]; x[i2+1] = xw[1]; x[i2+2] = xw[2]; x[i2+3] = xw[3]; x[i2+4] = xw[4]; 279 idiag += 25; 280 i2 += 5; 281 } 282 break; 283 case 6: 284 PetscKernel_v_gets_A_times_w_6(x,idiag,b); 285 t[0] = b[0]; t[1] = b[1]; t[2] = b[2]; t[3] = b[3]; t[4] = b[4]; t[5] = b[5]; 286 i2 = 6; 287 idiag += 36; 288 for (i=1; i<m; i++) { 289 v = aa + 36*ai[i]; 290 vi = aj + ai[i]; 291 nz = diag[i] - ai[i]; 292 s[0] = b[i2]; s[1] = b[i2+1]; s[2] = b[i2+2]; s[3] = b[i2+3]; s[4] = b[i2+4]; s[5] = b[i2+5]; 293 while (nz--) { 294 idx = 6*(*vi++); 295 xw[0] = x[idx]; xw[1] = x[1+idx]; xw[2] = x[2+idx]; 296 xw[3] = x[3+idx]; xw[4] = x[4+idx]; xw[5] = x[5+idx]; 297 PetscKernel_v_gets_v_minus_A_times_w_6(s,v,xw); 298 v += 36; 299 } 300 t[i2] = s[0]; t[i2+1] = s[1]; t[i2+2] = s[2]; 301 t[i2+3] = s[3]; t[i2+4] = s[4]; t[i2+5] = s[5]; 302 PetscKernel_v_gets_A_times_w_6(xw,idiag,s); 303 x[i2] = xw[0]; x[i2+1] = xw[1]; x[i2+2] = xw[2]; x[i2+3] = xw[3]; x[i2+4] = xw[4]; x[i2+5] = xw[5]; 304 idiag += 36; 305 i2 += 6; 306 } 307 break; 308 case 7: 309 PetscKernel_v_gets_A_times_w_7(x,idiag,b); 310 t[0] = b[0]; t[1] = b[1]; t[2] = b[2]; 311 t[3] = b[3]; t[4] = b[4]; t[5] = b[5]; t[6] = b[6]; 312 i2 = 7; 313 idiag += 49; 314 for (i=1; i<m; i++) { 315 v = aa + 49*ai[i]; 316 vi = aj + ai[i]; 317 nz = diag[i] - ai[i]; 318 s[0] = b[i2]; s[1] = b[i2+1]; s[2] = b[i2+2]; 319 s[3] = b[i2+3]; s[4] = b[i2+4]; s[5] = b[i2+5]; s[6] = b[i2+6]; 320 while (nz--) { 321 idx = 7*(*vi++); 322 xw[0] = x[idx]; xw[1] = x[1+idx]; xw[2] = x[2+idx]; 323 xw[3] = x[3+idx]; xw[4] = x[4+idx]; xw[5] = x[5+idx]; xw[6] = x[6+idx]; 324 PetscKernel_v_gets_v_minus_A_times_w_7(s,v,xw); 325 v += 49; 326 } 327 t[i2] = s[0]; t[i2+1] = s[1]; t[i2+2] = s[2]; 328 t[i2+3] = s[3]; t[i2+4] = s[4]; t[i2+5] = s[5]; t[i2+6] = s[6]; 329 PetscKernel_v_gets_A_times_w_7(xw,idiag,s); 330 x[i2] = xw[0]; x[i2+1] = xw[1]; x[i2+2] = xw[2]; 331 x[i2+3] = xw[3]; x[i2+4] = xw[4]; x[i2+5] = xw[5]; x[i2+6] = xw[6]; 332 idiag += 49; 333 i2 += 7; 334 } 335 break; 336 default: 337 PetscKernel_w_gets_Ar_times_v(bs,bs,b,idiag,x); 338 ierr = PetscMemcpy(t,b,bs*sizeof(PetscScalar));CHKERRQ(ierr); 339 i2 = bs; 340 idiag += bs2; 341 for (i=1; i<m; i++) { 342 v = aa + bs2*ai[i]; 343 vi = aj + ai[i]; 344 nz = diag[i] - ai[i]; 345 346 ierr = PetscMemcpy(w,b+i2,bs*sizeof(PetscScalar));CHKERRQ(ierr); 347 /* copy all rows of x that are needed into contiguous space */ 348 workt = work; 349 for (j=0; j<nz; j++) { 350 ierr = PetscMemcpy(workt,x + bs*(*vi++),bs*sizeof(PetscScalar));CHKERRQ(ierr); 351 workt += bs; 352 } 353 PetscKernel_w_gets_w_minus_Ar_times_v(bs,bs*nz,w,v,work); 354 ierr = PetscMemcpy(t+i2,w,bs*sizeof(PetscScalar));CHKERRQ(ierr); 355 PetscKernel_w_gets_Ar_times_v(bs,bs,w,idiag,x+i2); 356 357 idiag += bs2; 358 i2 += bs; 359 } 360 break; 361 } 362 /* for logging purposes assume number of nonzero in lower half is 1/2 of total */ 363 ierr = PetscLogFlops(1.0*bs2*a->nz);CHKERRQ(ierr); 364 xb = t; 365 } 366 else xb = b; 367 if (flag & SOR_BACKWARD_SWEEP || flag & SOR_LOCAL_BACKWARD_SWEEP) { 368 idiag = a->idiag+bs2*(a->mbs-1); 369 i2 = bs * (m-1); 370 switch (bs) { 371 case 1: 372 s[0] = xb[i2]; 373 PetscKernel_v_gets_A_times_w_1(xw,idiag,s); 374 x[i2] = xw[0]; 375 i2 -= 1; 376 for (i=m-2; i>=0; i--) { 377 v = aa + (diag[i]+1); 378 vi = aj + diag[i] + 1; 379 nz = ai[i+1] - diag[i] - 1; 380 s[0] = xb[i2]; 381 for (j=0; j<nz; j++) { 382 xw[0] = x[vi[j]]; 383 PetscKernel_v_gets_v_minus_A_times_w_1(s,(v+j),xw); 384 } 385 PetscKernel_v_gets_A_times_w_1(xw,idiag,s); 386 x[i2] = xw[0]; 387 idiag -= 1; 388 i2 -= 1; 389 } 390 break; 391 case 2: 392 s[0] = xb[i2]; s[1] = xb[i2+1]; 393 PetscKernel_v_gets_A_times_w_2(xw,idiag,s); 394 x[i2] = xw[0]; x[i2+1] = xw[1]; 395 i2 -= 2; 396 idiag -= 4; 397 for (i=m-2; i>=0; i--) { 398 v = aa + 4*(diag[i] + 1); 399 vi = aj + diag[i] + 1; 400 nz = ai[i+1] - diag[i] - 1; 401 s[0] = xb[i2]; s[1] = xb[i2+1]; 402 for (j=0; j<nz; j++) { 403 idx = 2*vi[j]; 404 it = 4*j; 405 xw[0] = x[idx]; xw[1] = x[1+idx]; 406 PetscKernel_v_gets_v_minus_A_times_w_2(s,(v+it),xw); 407 } 408 PetscKernel_v_gets_A_times_w_2(xw,idiag,s); 409 x[i2] = xw[0]; x[i2+1] = xw[1]; 410 idiag -= 4; 411 i2 -= 2; 412 } 413 break; 414 case 3: 415 s[0] = xb[i2]; s[1] = xb[i2+1]; s[2] = xb[i2+2]; 416 PetscKernel_v_gets_A_times_w_3(xw,idiag,s); 417 x[i2] = xw[0]; x[i2+1] = xw[1]; x[i2+2] = xw[2]; 418 i2 -= 3; 419 idiag -= 9; 420 for (i=m-2; i>=0; i--) { 421 v = aa + 9*(diag[i]+1); 422 vi = aj + diag[i] + 1; 423 nz = ai[i+1] - diag[i] - 1; 424 s[0] = xb[i2]; s[1] = xb[i2+1]; s[2] = xb[i2+2]; 425 while (nz--) { 426 idx = 3*(*vi++); 427 xw[0] = x[idx]; xw[1] = x[1+idx]; xw[2] = x[2+idx]; 428 PetscKernel_v_gets_v_minus_A_times_w_3(s,v,xw); 429 v += 9; 430 } 431 PetscKernel_v_gets_A_times_w_3(xw,idiag,s); 432 x[i2] = xw[0]; x[i2+1] = xw[1]; x[i2+2] = xw[2]; 433 idiag -= 9; 434 i2 -= 3; 435 } 436 break; 437 case 4: 438 s[0] = xb[i2]; s[1] = xb[i2+1]; s[2] = xb[i2+2]; s[3] = xb[i2+3]; 439 PetscKernel_v_gets_A_times_w_4(xw,idiag,s); 440 x[i2] = xw[0]; x[i2+1] = xw[1]; x[i2+2] = xw[2]; x[i2+3] = xw[3]; 441 i2 -= 4; 442 idiag -= 16; 443 for (i=m-2; i>=0; i--) { 444 v = aa + 16*(diag[i]+1); 445 vi = aj + diag[i] + 1; 446 nz = ai[i+1] - diag[i] - 1; 447 s[0] = xb[i2]; s[1] = xb[i2+1]; s[2] = xb[i2+2]; s[3] = xb[i2+3]; 448 while (nz--) { 449 idx = 4*(*vi++); 450 xw[0] = x[idx]; xw[1] = x[1+idx]; xw[2] = x[2+idx]; xw[3] = x[3+idx]; 451 PetscKernel_v_gets_v_minus_A_times_w_4(s,v,xw); 452 v += 16; 453 } 454 PetscKernel_v_gets_A_times_w_4(xw,idiag,s); 455 x[i2] = xw[0]; x[i2+1] = xw[1]; x[i2+2] = xw[2]; x[i2+3] = xw[3]; 456 idiag -= 16; 457 i2 -= 4; 458 } 459 break; 460 case 5: 461 s[0] = xb[i2]; s[1] = xb[i2+1]; s[2] = xb[i2+2]; s[3] = xb[i2+3]; s[4] = xb[i2+4]; 462 PetscKernel_v_gets_A_times_w_5(xw,idiag,s); 463 x[i2] = xw[0]; x[i2+1] = xw[1]; x[i2+2] = xw[2]; x[i2+3] = xw[3]; x[i2+4] = xw[4]; 464 i2 -= 5; 465 idiag -= 25; 466 for (i=m-2; i>=0; i--) { 467 v = aa + 25*(diag[i]+1); 468 vi = aj + diag[i] + 1; 469 nz = ai[i+1] - diag[i] - 1; 470 s[0] = xb[i2]; s[1] = xb[i2+1]; s[2] = xb[i2+2]; s[3] = xb[i2+3]; s[4] = xb[i2+4]; 471 while (nz--) { 472 idx = 5*(*vi++); 473 xw[0] = x[idx]; xw[1] = x[1+idx]; xw[2] = x[2+idx]; xw[3] = x[3+idx]; xw[4] = x[4+idx]; 474 PetscKernel_v_gets_v_minus_A_times_w_5(s,v,xw); 475 v += 25; 476 } 477 PetscKernel_v_gets_A_times_w_5(xw,idiag,s); 478 x[i2] = xw[0]; x[i2+1] = xw[1]; x[i2+2] = xw[2]; x[i2+3] = xw[3]; x[i2+4] = xw[4]; 479 idiag -= 25; 480 i2 -= 5; 481 } 482 break; 483 case 6: 484 s[0] = xb[i2]; s[1] = xb[i2+1]; s[2] = xb[i2+2]; s[3] = xb[i2+3]; s[4] = xb[i2+4]; s[5] = xb[i2+5]; 485 PetscKernel_v_gets_A_times_w_6(xw,idiag,s); 486 x[i2] = xw[0]; x[i2+1] = xw[1]; x[i2+2] = xw[2]; x[i2+3] = xw[3]; x[i2+4] = xw[4]; x[i2+5] = xw[5]; 487 i2 -= 6; 488 idiag -= 36; 489 for (i=m-2; i>=0; i--) { 490 v = aa + 36*(diag[i]+1); 491 vi = aj + diag[i] + 1; 492 nz = ai[i+1] - diag[i] - 1; 493 s[0] = xb[i2]; s[1] = xb[i2+1]; s[2] = xb[i2+2]; s[3] = xb[i2+3]; s[4] = xb[i2+4]; s[5] = xb[i2+5]; 494 while (nz--) { 495 idx = 6*(*vi++); 496 xw[0] = x[idx]; xw[1] = x[1+idx]; xw[2] = x[2+idx]; 497 xw[3] = x[3+idx]; xw[4] = x[4+idx]; xw[5] = x[5+idx]; 498 PetscKernel_v_gets_v_minus_A_times_w_6(s,v,xw); 499 v += 36; 500 } 501 PetscKernel_v_gets_A_times_w_6(xw,idiag,s); 502 x[i2] = xw[0]; x[i2+1] = xw[1]; x[i2+2] = xw[2]; x[i2+3] = xw[3]; x[i2+4] = xw[4]; x[i2+5] = xw[5]; 503 idiag -= 36; 504 i2 -= 6; 505 } 506 break; 507 case 7: 508 s[0] = xb[i2]; s[1] = xb[i2+1]; s[2] = xb[i2+2]; 509 s[3] = xb[i2+3]; s[4] = xb[i2+4]; s[5] = xb[i2+5]; s[6] = xb[i2+6]; 510 PetscKernel_v_gets_A_times_w_7(x,idiag,b); 511 x[i2] = xw[0]; x[i2+1] = xw[1]; x[i2+2] = xw[2]; 512 x[i2+3] = xw[3]; x[i2+4] = xw[4]; x[i2+5] = xw[5]; x[i2+6] = xw[6]; 513 i2 -= 7; 514 idiag -= 49; 515 for (i=m-2; i>=0; i--) { 516 v = aa + 49*(diag[i]+1); 517 vi = aj + diag[i] + 1; 518 nz = ai[i+1] - diag[i] - 1; 519 s[0] = xb[i2]; s[1] = xb[i2+1]; s[2] = xb[i2+2]; 520 s[3] = xb[i2+3]; s[4] = xb[i2+4]; s[5] = xb[i2+5]; s[6] = xb[i2+6]; 521 while (nz--) { 522 idx = 7*(*vi++); 523 xw[0] = x[idx]; xw[1] = x[1+idx]; xw[2] = x[2+idx]; 524 xw[3] = x[3+idx]; xw[4] = x[4+idx]; xw[5] = x[5+idx]; xw[6] = x[6+idx]; 525 PetscKernel_v_gets_v_minus_A_times_w_7(s,v,xw); 526 v += 49; 527 } 528 PetscKernel_v_gets_A_times_w_7(xw,idiag,s); 529 x[i2] = xw[0]; x[i2+1] = xw[1]; x[i2+2] = xw[2]; 530 x[i2+3] = xw[3]; x[i2+4] = xw[4]; x[i2+5] = xw[5]; x[i2+6] = xw[6]; 531 idiag -= 49; 532 i2 -= 7; 533 } 534 break; 535 default: 536 ierr = PetscMemcpy(w,xb+i2,bs*sizeof(PetscScalar));CHKERRQ(ierr); 537 PetscKernel_w_gets_Ar_times_v(bs,bs,w,idiag,x+i2); 538 i2 -= bs; 539 idiag -= bs2; 540 for (i=m-2; i>=0; i--) { 541 v = aa + bs2*(diag[i]+1); 542 vi = aj + diag[i] + 1; 543 nz = ai[i+1] - diag[i] - 1; 544 545 ierr = PetscMemcpy(w,xb+i2,bs*sizeof(PetscScalar));CHKERRQ(ierr); 546 /* copy all rows of x that are needed into contiguous space */ 547 workt = work; 548 for (j=0; j<nz; j++) { 549 ierr = PetscMemcpy(workt,x + bs*(*vi++),bs*sizeof(PetscScalar));CHKERRQ(ierr); 550 workt += bs; 551 } 552 PetscKernel_w_gets_w_minus_Ar_times_v(bs,bs*nz,w,v,work); 553 PetscKernel_w_gets_Ar_times_v(bs,bs,w,idiag,x+i2); 554 555 idiag -= bs2; 556 i2 -= bs; 557 } 558 break; 559 } 560 ierr = PetscLogFlops(1.0*bs2*(a->nz));CHKERRQ(ierr); 561 } 562 its--; 563 } 564 while (its--) { 565 if (flag & SOR_FORWARD_SWEEP || flag & SOR_LOCAL_FORWARD_SWEEP) { 566 idiag = a->idiag; 567 i2 = 0; 568 switch (bs) { 569 case 1: 570 for (i=0; i<m; i++) { 571 v = aa + ai[i]; 572 vi = aj + ai[i]; 573 nz = ai[i+1] - ai[i]; 574 s[0] = b[i2]; 575 for (j=0; j<nz; j++) { 576 xw[0] = x[vi[j]]; 577 PetscKernel_v_gets_v_minus_A_times_w_1(s,(v+j),xw); 578 } 579 PetscKernel_v_gets_A_times_w_1(xw,idiag,s); 580 x[i2] += xw[0]; 581 idiag += 1; 582 i2 += 1; 583 } 584 break; 585 case 2: 586 for (i=0; i<m; i++) { 587 v = aa + 4*ai[i]; 588 vi = aj + ai[i]; 589 nz = ai[i+1] - ai[i]; 590 s[0] = b[i2]; s[1] = b[i2+1]; 591 for (j=0; j<nz; j++) { 592 idx = 2*vi[j]; 593 it = 4*j; 594 xw[0] = x[idx]; xw[1] = x[1+idx]; 595 PetscKernel_v_gets_v_minus_A_times_w_2(s,(v+it),xw); 596 } 597 PetscKernel_v_gets_A_times_w_2(xw,idiag,s); 598 x[i2] += xw[0]; x[i2+1] += xw[1]; 599 idiag += 4; 600 i2 += 2; 601 } 602 break; 603 case 3: 604 for (i=0; i<m; i++) { 605 v = aa + 9*ai[i]; 606 vi = aj + ai[i]; 607 nz = ai[i+1] - ai[i]; 608 s[0] = b[i2]; s[1] = b[i2+1]; s[2] = b[i2+2]; 609 while (nz--) { 610 idx = 3*(*vi++); 611 xw[0] = x[idx]; xw[1] = x[1+idx]; xw[2] = x[2+idx]; 612 PetscKernel_v_gets_v_minus_A_times_w_3(s,v,xw); 613 v += 9; 614 } 615 PetscKernel_v_gets_A_times_w_3(xw,idiag,s); 616 x[i2] += xw[0]; x[i2+1] += xw[1]; x[i2+2] += xw[2]; 617 idiag += 9; 618 i2 += 3; 619 } 620 break; 621 case 4: 622 for (i=0; i<m; i++) { 623 v = aa + 16*ai[i]; 624 vi = aj + ai[i]; 625 nz = ai[i+1] - ai[i]; 626 s[0] = b[i2]; s[1] = b[i2+1]; s[2] = b[i2+2]; s[3] = b[i2+3]; 627 while (nz--) { 628 idx = 4*(*vi++); 629 xw[0] = x[idx]; xw[1] = x[1+idx]; xw[2] = x[2+idx]; xw[3] = x[3+idx]; 630 PetscKernel_v_gets_v_minus_A_times_w_4(s,v,xw); 631 v += 16; 632 } 633 PetscKernel_v_gets_A_times_w_4(xw,idiag,s); 634 x[i2] += xw[0]; x[i2+1] += xw[1]; x[i2+2] += xw[2]; x[i2+3] += xw[3]; 635 idiag += 16; 636 i2 += 4; 637 } 638 break; 639 case 5: 640 for (i=0; i<m; i++) { 641 v = aa + 25*ai[i]; 642 vi = aj + ai[i]; 643 nz = ai[i+1] - ai[i]; 644 s[0] = b[i2]; s[1] = b[i2+1]; s[2] = b[i2+2]; s[3] = b[i2+3]; s[4] = b[i2+4]; 645 while (nz--) { 646 idx = 5*(*vi++); 647 xw[0] = x[idx]; xw[1] = x[1+idx]; xw[2] = x[2+idx]; xw[3] = x[3+idx]; xw[4] = x[4+idx]; 648 PetscKernel_v_gets_v_minus_A_times_w_5(s,v,xw); 649 v += 25; 650 } 651 PetscKernel_v_gets_A_times_w_5(xw,idiag,s); 652 x[i2] += xw[0]; x[i2+1] += xw[1]; x[i2+2] += xw[2]; x[i2+3] += xw[3]; x[i2+4] += xw[4]; 653 idiag += 25; 654 i2 += 5; 655 } 656 break; 657 case 6: 658 for (i=0; i<m; i++) { 659 v = aa + 36*ai[i]; 660 vi = aj + ai[i]; 661 nz = ai[i+1] - ai[i]; 662 s[0] = b[i2]; s[1] = b[i2+1]; s[2] = b[i2+2]; s[3] = b[i2+3]; s[4] = b[i2+4]; s[5] = b[i2+5]; 663 while (nz--) { 664 idx = 6*(*vi++); 665 xw[0] = x[idx]; xw[1] = x[1+idx]; xw[2] = x[2+idx]; 666 xw[3] = x[3+idx]; xw[4] = x[4+idx]; xw[5] = x[5+idx]; 667 PetscKernel_v_gets_v_minus_A_times_w_6(s,v,xw); 668 v += 36; 669 } 670 PetscKernel_v_gets_A_times_w_6(xw,idiag,s); 671 x[i2] += xw[0]; x[i2+1] += xw[1]; x[i2+2] += xw[2]; 672 x[i2+3] += xw[3]; x[i2+4] += xw[4]; x[i2+5] += xw[5]; 673 idiag += 36; 674 i2 += 6; 675 } 676 break; 677 case 7: 678 for (i=0; i<m; i++) { 679 v = aa + 49*ai[i]; 680 vi = aj + ai[i]; 681 nz = ai[i+1] - ai[i]; 682 s[0] = b[i2]; s[1] = b[i2+1]; s[2] = b[i2+2]; 683 s[3] = b[i2+3]; s[4] = b[i2+4]; s[5] = b[i2+5]; s[6] = b[i2+6]; 684 while (nz--) { 685 idx = 7*(*vi++); 686 xw[0] = x[idx]; xw[1] = x[1+idx]; xw[2] = x[2+idx]; 687 xw[3] = x[3+idx]; xw[4] = x[4+idx]; xw[5] = x[5+idx]; xw[6] = x[6+idx]; 688 PetscKernel_v_gets_v_minus_A_times_w_7(s,v,xw); 689 v += 49; 690 } 691 PetscKernel_v_gets_A_times_w_7(xw,idiag,s); 692 x[i2] += xw[0]; x[i2+1] += xw[1]; x[i2+2] += xw[2]; 693 x[i2+3] += xw[3]; x[i2+4] += xw[4]; x[i2+5] += xw[5]; x[i2+6] += xw[6]; 694 idiag += 49; 695 i2 += 7; 696 } 697 break; 698 default: 699 for (i=0; i<m; i++) { 700 v = aa + bs2*ai[i]; 701 vi = aj + ai[i]; 702 nz = ai[i+1] - ai[i]; 703 704 ierr = PetscMemcpy(w,b+i2,bs*sizeof(PetscScalar));CHKERRQ(ierr); 705 /* copy all rows of x that are needed into contiguous space */ 706 workt = work; 707 for (j=0; j<nz; j++) { 708 ierr = PetscMemcpy(workt,x + bs*(*vi++),bs*sizeof(PetscScalar));CHKERRQ(ierr); 709 workt += bs; 710 } 711 PetscKernel_w_gets_w_minus_Ar_times_v(bs,bs*nz,w,v,work); 712 PetscKernel_w_gets_w_plus_Ar_times_v(bs,bs,w,idiag,x+i2); 713 714 idiag += bs2; 715 i2 += bs; 716 } 717 break; 718 } 719 ierr = PetscLogFlops(2.0*bs2*a->nz);CHKERRQ(ierr); 720 } 721 if (flag & SOR_BACKWARD_SWEEP || flag & SOR_LOCAL_BACKWARD_SWEEP) { 722 idiag = a->idiag+bs2*(a->mbs-1); 723 i2 = bs * (m-1); 724 switch (bs) { 725 case 1: 726 for (i=m-1; i>=0; i--) { 727 v = aa + ai[i]; 728 vi = aj + ai[i]; 729 nz = ai[i+1] - ai[i]; 730 s[0] = b[i2]; 731 for (j=0; j<nz; j++) { 732 xw[0] = x[vi[j]]; 733 PetscKernel_v_gets_v_minus_A_times_w_1(s,(v+j),xw); 734 } 735 PetscKernel_v_gets_A_times_w_1(xw,idiag,s); 736 x[i2] += xw[0]; 737 idiag -= 1; 738 i2 -= 1; 739 } 740 break; 741 case 2: 742 for (i=m-1; i>=0; i--) { 743 v = aa + 4*ai[i]; 744 vi = aj + ai[i]; 745 nz = ai[i+1] - ai[i]; 746 s[0] = b[i2]; s[1] = b[i2+1]; 747 for (j=0; j<nz; j++) { 748 idx = 2*vi[j]; 749 it = 4*j; 750 xw[0] = x[idx]; xw[1] = x[1+idx]; 751 PetscKernel_v_gets_v_minus_A_times_w_2(s,(v+it),xw); 752 } 753 PetscKernel_v_gets_A_times_w_2(xw,idiag,s); 754 x[i2] += xw[0]; x[i2+1] += xw[1]; 755 idiag -= 4; 756 i2 -= 2; 757 } 758 break; 759 case 3: 760 for (i=m-1; i>=0; i--) { 761 v = aa + 9*ai[i]; 762 vi = aj + ai[i]; 763 nz = ai[i+1] - ai[i]; 764 s[0] = b[i2]; s[1] = b[i2+1]; s[2] = b[i2+2]; 765 while (nz--) { 766 idx = 3*(*vi++); 767 xw[0] = x[idx]; xw[1] = x[1+idx]; xw[2] = x[2+idx]; 768 PetscKernel_v_gets_v_minus_A_times_w_3(s,v,xw); 769 v += 9; 770 } 771 PetscKernel_v_gets_A_times_w_3(xw,idiag,s); 772 x[i2] += xw[0]; x[i2+1] += xw[1]; x[i2+2] += xw[2]; 773 idiag -= 9; 774 i2 -= 3; 775 } 776 break; 777 case 4: 778 for (i=m-1; i>=0; i--) { 779 v = aa + 16*ai[i]; 780 vi = aj + ai[i]; 781 nz = ai[i+1] - ai[i]; 782 s[0] = b[i2]; s[1] = b[i2+1]; s[2] = b[i2+2]; s[3] = b[i2+3]; 783 while (nz--) { 784 idx = 4*(*vi++); 785 xw[0] = x[idx]; xw[1] = x[1+idx]; xw[2] = x[2+idx]; xw[3] = x[3+idx]; 786 PetscKernel_v_gets_v_minus_A_times_w_4(s,v,xw); 787 v += 16; 788 } 789 PetscKernel_v_gets_A_times_w_4(xw,idiag,s); 790 x[i2] += xw[0]; x[i2+1] += xw[1]; x[i2+2] += xw[2]; x[i2+3] += xw[3]; 791 idiag -= 16; 792 i2 -= 4; 793 } 794 break; 795 case 5: 796 for (i=m-1; i>=0; i--) { 797 v = aa + 25*ai[i]; 798 vi = aj + ai[i]; 799 nz = ai[i+1] - ai[i]; 800 s[0] = b[i2]; s[1] = b[i2+1]; s[2] = b[i2+2]; s[3] = b[i2+3]; s[4] = b[i2+4]; 801 while (nz--) { 802 idx = 5*(*vi++); 803 xw[0] = x[idx]; xw[1] = x[1+idx]; xw[2] = x[2+idx]; xw[3] = x[3+idx]; xw[4] = x[4+idx]; 804 PetscKernel_v_gets_v_minus_A_times_w_5(s,v,xw); 805 v += 25; 806 } 807 PetscKernel_v_gets_A_times_w_5(xw,idiag,s); 808 x[i2] += xw[0]; x[i2+1] += xw[1]; x[i2+2] += xw[2]; x[i2+3] += xw[3]; x[i2+4] += xw[4]; 809 idiag -= 25; 810 i2 -= 5; 811 } 812 break; 813 case 6: 814 for (i=m-1; i>=0; i--) { 815 v = aa + 36*ai[i]; 816 vi = aj + ai[i]; 817 nz = ai[i+1] - ai[i]; 818 s[0] = b[i2]; s[1] = b[i2+1]; s[2] = b[i2+2]; s[3] = b[i2+3]; s[4] = b[i2+4]; s[5] = b[i2+5]; 819 while (nz--) { 820 idx = 6*(*vi++); 821 xw[0] = x[idx]; xw[1] = x[1+idx]; xw[2] = x[2+idx]; 822 xw[3] = x[3+idx]; xw[4] = x[4+idx]; xw[5] = x[5+idx]; 823 PetscKernel_v_gets_v_minus_A_times_w_6(s,v,xw); 824 v += 36; 825 } 826 PetscKernel_v_gets_A_times_w_6(xw,idiag,s); 827 x[i2] += xw[0]; x[i2+1] += xw[1]; x[i2+2] += xw[2]; 828 x[i2+3] += xw[3]; x[i2+4] += xw[4]; x[i2+5] += xw[5]; 829 idiag -= 36; 830 i2 -= 6; 831 } 832 break; 833 case 7: 834 for (i=m-1; i>=0; i--) { 835 v = aa + 49*ai[i]; 836 vi = aj + ai[i]; 837 nz = ai[i+1] - ai[i]; 838 s[0] = b[i2]; s[1] = b[i2+1]; s[2] = b[i2+2]; 839 s[3] = b[i2+3]; s[4] = b[i2+4]; s[5] = b[i2+5]; s[6] = b[i2+6]; 840 while (nz--) { 841 idx = 7*(*vi++); 842 xw[0] = x[idx]; xw[1] = x[1+idx]; xw[2] = x[2+idx]; 843 xw[3] = x[3+idx]; xw[4] = x[4+idx]; xw[5] = x[5+idx]; xw[6] = x[6+idx]; 844 PetscKernel_v_gets_v_minus_A_times_w_7(s,v,xw); 845 v += 49; 846 } 847 PetscKernel_v_gets_A_times_w_7(xw,idiag,s); 848 x[i2] += xw[0]; x[i2+1] += xw[1]; x[i2+2] += xw[2]; 849 x[i2+3] += xw[3]; x[i2+4] += xw[4]; x[i2+5] += xw[5]; x[i2+6] += xw[6]; 850 idiag -= 49; 851 i2 -= 7; 852 } 853 break; 854 default: 855 for (i=m-1; i>=0; i--) { 856 v = aa + bs2*ai[i]; 857 vi = aj + ai[i]; 858 nz = ai[i+1] - ai[i]; 859 860 ierr = PetscMemcpy(w,b+i2,bs*sizeof(PetscScalar));CHKERRQ(ierr); 861 /* copy all rows of x that are needed into contiguous space */ 862 workt = work; 863 for (j=0; j<nz; j++) { 864 ierr = PetscMemcpy(workt,x + bs*(*vi++),bs*sizeof(PetscScalar));CHKERRQ(ierr); 865 workt += bs; 866 } 867 PetscKernel_w_gets_w_minus_Ar_times_v(bs,bs*nz,w,v,work); 868 PetscKernel_w_gets_w_plus_Ar_times_v(bs,bs,w,idiag,x+i2); 869 870 idiag -= bs2; 871 i2 -= bs; 872 } 873 break; 874 } 875 ierr = PetscLogFlops(2.0*bs2*(a->nz));CHKERRQ(ierr); 876 } 877 } 878 ierr = VecRestoreArray(xx,&x);CHKERRQ(ierr); 879 ierr = VecRestoreArrayRead(bb,&b);CHKERRQ(ierr); 880 PetscFunctionReturn(0); 881 } 882 883 884 /* 885 Special version for direct calls from Fortran (Used in PETSc-fun3d) 886 */ 887 #if defined(PETSC_HAVE_FORTRAN_CAPS) 888 #define matsetvaluesblocked4_ MATSETVALUESBLOCKED4 889 #elif !defined(PETSC_HAVE_FORTRAN_UNDERSCORE) 890 #define matsetvaluesblocked4_ matsetvaluesblocked4 891 #endif 892 893 #undef __FUNCT__ 894 #define __FUNCT__ "matsetvaluesblocked4_" 895 PETSC_EXTERN void matsetvaluesblocked4_(Mat *AA,PetscInt *mm,const PetscInt im[],PetscInt *nn,const PetscInt in[],const PetscScalar v[]) 896 { 897 Mat A = *AA; 898 Mat_SeqBAIJ *a = (Mat_SeqBAIJ*)A->data; 899 PetscInt *rp,k,low,high,t,ii,jj,row,nrow,i,col,l,N,m = *mm,n = *nn; 900 PetscInt *ai =a->i,*ailen=a->ilen; 901 PetscInt *aj =a->j,stepval,lastcol = -1; 902 const PetscScalar *value = v; 903 MatScalar *ap,*aa = a->a,*bap; 904 905 PetscFunctionBegin; 906 if (A->rmap->bs != 4) SETERRABORT(PetscObjectComm((PetscObject)A),PETSC_ERR_ARG_WRONG,"Can only be called with a block size of 4"); 907 stepval = (n-1)*4; 908 for (k=0; k<m; k++) { /* loop over added rows */ 909 row = im[k]; 910 rp = aj + ai[row]; 911 ap = aa + 16*ai[row]; 912 nrow = ailen[row]; 913 low = 0; 914 high = nrow; 915 for (l=0; l<n; l++) { /* loop over added columns */ 916 col = in[l]; 917 if (col <= lastcol) low = 0; 918 else high = nrow; 919 lastcol = col; 920 value = v + k*(stepval+4 + l)*4; 921 while (high-low > 7) { 922 t = (low+high)/2; 923 if (rp[t] > col) high = t; 924 else low = t; 925 } 926 for (i=low; i<high; i++) { 927 if (rp[i] > col) break; 928 if (rp[i] == col) { 929 bap = ap + 16*i; 930 for (ii=0; ii<4; ii++,value+=stepval) { 931 for (jj=ii; jj<16; jj+=4) { 932 bap[jj] += *value++; 933 } 934 } 935 goto noinsert2; 936 } 937 } 938 N = nrow++ - 1; 939 high++; /* added new column index thus must search to one higher than before */ 940 /* shift up all the later entries in this row */ 941 for (ii=N; ii>=i; ii--) { 942 rp[ii+1] = rp[ii]; 943 PetscMemcpy(ap+16*(ii+1),ap+16*(ii),16*sizeof(MatScalar)); 944 } 945 if (N >= i) { 946 PetscMemzero(ap+16*i,16*sizeof(MatScalar)); 947 } 948 rp[i] = col; 949 bap = ap + 16*i; 950 for (ii=0; ii<4; ii++,value+=stepval) { 951 for (jj=ii; jj<16; jj+=4) { 952 bap[jj] = *value++; 953 } 954 } 955 noinsert2:; 956 low = i; 957 } 958 ailen[row] = nrow; 959 } 960 PetscFunctionReturnVoid(); 961 } 962 963 #if defined(PETSC_HAVE_FORTRAN_CAPS) 964 #define matsetvalues4_ MATSETVALUES4 965 #elif !defined(PETSC_HAVE_FORTRAN_UNDERSCORE) 966 #define matsetvalues4_ matsetvalues4 967 #endif 968 969 #undef __FUNCT__ 970 #define __FUNCT__ "MatSetValues4_" 971 PETSC_EXTERN void matsetvalues4_(Mat *AA,PetscInt *mm,PetscInt *im,PetscInt *nn,PetscInt *in,PetscScalar *v) 972 { 973 Mat A = *AA; 974 Mat_SeqBAIJ *a = (Mat_SeqBAIJ*)A->data; 975 PetscInt *rp,k,low,high,t,ii,row,nrow,i,col,l,N,n = *nn,m = *mm; 976 PetscInt *ai=a->i,*ailen=a->ilen; 977 PetscInt *aj=a->j,brow,bcol; 978 PetscInt ridx,cidx,lastcol = -1; 979 MatScalar *ap,value,*aa=a->a,*bap; 980 981 PetscFunctionBegin; 982 for (k=0; k<m; k++) { /* loop over added rows */ 983 row = im[k]; brow = row/4; 984 rp = aj + ai[brow]; 985 ap = aa + 16*ai[brow]; 986 nrow = ailen[brow]; 987 low = 0; 988 high = nrow; 989 for (l=0; l<n; l++) { /* loop over added columns */ 990 col = in[l]; bcol = col/4; 991 ridx = row % 4; cidx = col % 4; 992 value = v[l + k*n]; 993 if (col <= lastcol) low = 0; 994 else high = nrow; 995 lastcol = col; 996 while (high-low > 7) { 997 t = (low+high)/2; 998 if (rp[t] > bcol) high = t; 999 else low = t; 1000 } 1001 for (i=low; i<high; i++) { 1002 if (rp[i] > bcol) break; 1003 if (rp[i] == bcol) { 1004 bap = ap + 16*i + 4*cidx + ridx; 1005 *bap += value; 1006 goto noinsert1; 1007 } 1008 } 1009 N = nrow++ - 1; 1010 high++; /* added new column thus must search to one higher than before */ 1011 /* shift up all the later entries in this row */ 1012 for (ii=N; ii>=i; ii--) { 1013 rp[ii+1] = rp[ii]; 1014 PetscMemcpy(ap+16*(ii+1),ap+16*(ii),16*sizeof(MatScalar)); 1015 } 1016 if (N>=i) { 1017 PetscMemzero(ap+16*i,16*sizeof(MatScalar)); 1018 } 1019 rp[i] = bcol; 1020 ap[16*i + 4*cidx + ridx] = value; 1021 noinsert1:; 1022 low = i; 1023 } 1024 ailen[brow] = nrow; 1025 } 1026 PetscFunctionReturnVoid(); 1027 } 1028 1029 /* 1030 Checks for missing diagonals 1031 */ 1032 #undef __FUNCT__ 1033 #define __FUNCT__ "MatMissingDiagonal_SeqBAIJ" 1034 PetscErrorCode MatMissingDiagonal_SeqBAIJ(Mat A,PetscBool *missing,PetscInt *d) 1035 { 1036 Mat_SeqBAIJ *a = (Mat_SeqBAIJ*)A->data; 1037 PetscErrorCode ierr; 1038 PetscInt *diag,*ii = a->i,i; 1039 1040 PetscFunctionBegin; 1041 ierr = MatMarkDiagonal_SeqBAIJ(A);CHKERRQ(ierr); 1042 *missing = PETSC_FALSE; 1043 if (A->rmap->n > 0 && !ii) { 1044 *missing = PETSC_TRUE; 1045 if (d) *d = 0; 1046 PetscInfo(A,"Matrix has no entries therefore is missing diagonal"); 1047 } else { 1048 diag = a->diag; 1049 for (i=0; i<a->mbs; i++) { 1050 if (diag[i] >= ii[i+1]) { 1051 *missing = PETSC_TRUE; 1052 if (d) *d = i; 1053 PetscInfo1(A,"Matrix is missing block diagonal number %D",i); 1054 break; 1055 } 1056 } 1057 } 1058 PetscFunctionReturn(0); 1059 } 1060 1061 #undef __FUNCT__ 1062 #define __FUNCT__ "MatMarkDiagonal_SeqBAIJ" 1063 PetscErrorCode MatMarkDiagonal_SeqBAIJ(Mat A) 1064 { 1065 Mat_SeqBAIJ *a = (Mat_SeqBAIJ*)A->data; 1066 PetscErrorCode ierr; 1067 PetscInt i,j,m = a->mbs; 1068 1069 PetscFunctionBegin; 1070 if (!a->diag) { 1071 ierr = PetscMalloc1(m,&a->diag);CHKERRQ(ierr); 1072 ierr = PetscLogObjectMemory((PetscObject)A,m*sizeof(PetscInt));CHKERRQ(ierr); 1073 a->free_diag = PETSC_TRUE; 1074 } 1075 for (i=0; i<m; i++) { 1076 a->diag[i] = a->i[i+1]; 1077 for (j=a->i[i]; j<a->i[i+1]; j++) { 1078 if (a->j[j] == i) { 1079 a->diag[i] = j; 1080 break; 1081 } 1082 } 1083 } 1084 PetscFunctionReturn(0); 1085 } 1086 1087 1088 #undef __FUNCT__ 1089 #define __FUNCT__ "MatGetRowIJ_SeqBAIJ" 1090 static PetscErrorCode MatGetRowIJ_SeqBAIJ(Mat A,PetscInt oshift,PetscBool symmetric,PetscBool blockcompressed,PetscInt *nn,const PetscInt *inia[],const PetscInt *inja[],PetscBool *done) 1091 { 1092 Mat_SeqBAIJ *a = (Mat_SeqBAIJ*)A->data; 1093 PetscErrorCode ierr; 1094 PetscInt i,j,n = a->mbs,nz = a->i[n],*tia,*tja,bs = A->rmap->bs,k,l,cnt; 1095 PetscInt **ia = (PetscInt**)inia,**ja = (PetscInt**)inja; 1096 1097 PetscFunctionBegin; 1098 *nn = n; 1099 if (!ia) PetscFunctionReturn(0); 1100 if (symmetric) { 1101 ierr = MatToSymmetricIJ_SeqAIJ(n,a->i,a->j,0,0,&tia,&tja);CHKERRQ(ierr); 1102 nz = tia[n]; 1103 } else { 1104 tia = a->i; tja = a->j; 1105 } 1106 1107 if (!blockcompressed && bs > 1) { 1108 (*nn) *= bs; 1109 /* malloc & create the natural set of indices */ 1110 ierr = PetscMalloc1((n+1)*bs,ia);CHKERRQ(ierr); 1111 if (n) { 1112 (*ia)[0] = 0; 1113 for (j=1; j<bs; j++) { 1114 (*ia)[j] = (tia[1]-tia[0])*bs+(*ia)[j-1]; 1115 } 1116 } 1117 1118 for (i=1; i<n; i++) { 1119 (*ia)[i*bs] = (tia[i]-tia[i-1])*bs + (*ia)[i*bs-1]; 1120 for (j=1; j<bs; j++) { 1121 (*ia)[i*bs+j] = (tia[i+1]-tia[i])*bs + (*ia)[i*bs+j-1]; 1122 } 1123 } 1124 if (n) { 1125 (*ia)[n*bs] = (tia[n]-tia[n-1])*bs + (*ia)[n*bs-1]; 1126 } 1127 1128 if (inja) { 1129 ierr = PetscMalloc1(nz*bs*bs,ja);CHKERRQ(ierr); 1130 cnt = 0; 1131 for (i=0; i<n; i++) { 1132 for (j=0; j<bs; j++) { 1133 for (k=tia[i]; k<tia[i+1]; k++) { 1134 for (l=0; l<bs; l++) { 1135 (*ja)[cnt++] = bs*tja[k] + l; 1136 } 1137 } 1138 } 1139 } 1140 } 1141 1142 if (symmetric) { /* deallocate memory allocated in MatToSymmetricIJ_SeqAIJ() */ 1143 ierr = PetscFree(tia);CHKERRQ(ierr); 1144 ierr = PetscFree(tja);CHKERRQ(ierr); 1145 } 1146 } else if (oshift == 1) { 1147 if (symmetric) { 1148 nz = tia[A->rmap->n/bs]; 1149 /* add 1 to i and j indices */ 1150 for (i=0; i<A->rmap->n/bs+1; i++) tia[i] = tia[i] + 1; 1151 *ia = tia; 1152 if (ja) { 1153 for (i=0; i<nz; i++) tja[i] = tja[i] + 1; 1154 *ja = tja; 1155 } 1156 } else { 1157 nz = a->i[A->rmap->n/bs]; 1158 /* malloc space and add 1 to i and j indices */ 1159 ierr = PetscMalloc1((A->rmap->n/bs+1),ia);CHKERRQ(ierr); 1160 for (i=0; i<A->rmap->n/bs+1; i++) (*ia)[i] = a->i[i] + 1; 1161 if (ja) { 1162 ierr = PetscMalloc1(nz,ja);CHKERRQ(ierr); 1163 for (i=0; i<nz; i++) (*ja)[i] = a->j[i] + 1; 1164 } 1165 } 1166 } else { 1167 *ia = tia; 1168 if (ja) *ja = tja; 1169 } 1170 PetscFunctionReturn(0); 1171 } 1172 1173 #undef __FUNCT__ 1174 #define __FUNCT__ "MatRestoreRowIJ_SeqBAIJ" 1175 static PetscErrorCode MatRestoreRowIJ_SeqBAIJ(Mat A,PetscInt oshift,PetscBool symmetric,PetscBool blockcompressed,PetscInt *nn,const PetscInt *ia[],const PetscInt *ja[],PetscBool *done) 1176 { 1177 PetscErrorCode ierr; 1178 1179 PetscFunctionBegin; 1180 if (!ia) PetscFunctionReturn(0); 1181 if ((!blockcompressed && A->rmap->bs > 1) || (symmetric || oshift == 1)) { 1182 ierr = PetscFree(*ia);CHKERRQ(ierr); 1183 if (ja) {ierr = PetscFree(*ja);CHKERRQ(ierr);} 1184 } 1185 PetscFunctionReturn(0); 1186 } 1187 1188 #undef __FUNCT__ 1189 #define __FUNCT__ "MatDestroy_SeqBAIJ" 1190 PetscErrorCode MatDestroy_SeqBAIJ(Mat A) 1191 { 1192 Mat_SeqBAIJ *a = (Mat_SeqBAIJ*)A->data; 1193 PetscErrorCode ierr; 1194 1195 PetscFunctionBegin; 1196 #if defined(PETSC_USE_LOG) 1197 PetscLogObjectState((PetscObject)A,"Rows=%D, Cols=%D, NZ=%D",A->rmap->N,A->cmap->n,a->nz); 1198 #endif 1199 ierr = MatSeqXAIJFreeAIJ(A,&a->a,&a->j,&a->i);CHKERRQ(ierr); 1200 ierr = ISDestroy(&a->row);CHKERRQ(ierr); 1201 ierr = ISDestroy(&a->col);CHKERRQ(ierr); 1202 if (a->free_diag) {ierr = PetscFree(a->diag);CHKERRQ(ierr);} 1203 ierr = PetscFree(a->idiag);CHKERRQ(ierr); 1204 if (a->free_imax_ilen) {ierr = PetscFree2(a->imax,a->ilen);CHKERRQ(ierr);} 1205 ierr = PetscFree(a->solve_work);CHKERRQ(ierr); 1206 ierr = PetscFree(a->mult_work);CHKERRQ(ierr); 1207 ierr = PetscFree(a->sor_work);CHKERRQ(ierr); 1208 ierr = ISDestroy(&a->icol);CHKERRQ(ierr); 1209 ierr = PetscFree(a->saved_values);CHKERRQ(ierr); 1210 ierr = PetscFree(a->xtoy);CHKERRQ(ierr); 1211 ierr = PetscFree2(a->compressedrow.i,a->compressedrow.rindex);CHKERRQ(ierr); 1212 1213 ierr = MatDestroy(&a->sbaijMat);CHKERRQ(ierr); 1214 ierr = MatDestroy(&a->parent);CHKERRQ(ierr); 1215 ierr = PetscFree(A->data);CHKERRQ(ierr); 1216 1217 ierr = PetscObjectChangeTypeName((PetscObject)A,0);CHKERRQ(ierr); 1218 ierr = PetscObjectComposeFunction((PetscObject)A,"MatInvertBlockDiagonal_C",NULL);CHKERRQ(ierr); 1219 ierr = PetscObjectComposeFunction((PetscObject)A,"MatStoreValues_C",NULL);CHKERRQ(ierr); 1220 ierr = PetscObjectComposeFunction((PetscObject)A,"MatRetrieveValues_C",NULL);CHKERRQ(ierr); 1221 ierr = PetscObjectComposeFunction((PetscObject)A,"MatSeqBAIJSetColumnIndices_C",NULL);CHKERRQ(ierr); 1222 ierr = PetscObjectComposeFunction((PetscObject)A,"MatConvert_seqbaij_seqaij_C",NULL);CHKERRQ(ierr); 1223 ierr = PetscObjectComposeFunction((PetscObject)A,"MatConvert_seqbaij_seqsbaij_C",NULL);CHKERRQ(ierr); 1224 ierr = PetscObjectComposeFunction((PetscObject)A,"MatSeqBAIJSetPreallocation_C",NULL);CHKERRQ(ierr); 1225 ierr = PetscObjectComposeFunction((PetscObject)A,"MatSeqBAIJSetPreallocationCSR_C",NULL);CHKERRQ(ierr); 1226 ierr = PetscObjectComposeFunction((PetscObject)A,"MatConvert_seqbaij_seqbstrm_C",NULL);CHKERRQ(ierr); 1227 ierr = PetscObjectComposeFunction((PetscObject)A,"MatIsTranspose_C",NULL);CHKERRQ(ierr); 1228 PetscFunctionReturn(0); 1229 } 1230 1231 #undef __FUNCT__ 1232 #define __FUNCT__ "MatSetOption_SeqBAIJ" 1233 PetscErrorCode MatSetOption_SeqBAIJ(Mat A,MatOption op,PetscBool flg) 1234 { 1235 Mat_SeqBAIJ *a = (Mat_SeqBAIJ*)A->data; 1236 PetscErrorCode ierr; 1237 1238 PetscFunctionBegin; 1239 switch (op) { 1240 case MAT_ROW_ORIENTED: 1241 a->roworiented = flg; 1242 break; 1243 case MAT_KEEP_NONZERO_PATTERN: 1244 a->keepnonzeropattern = flg; 1245 break; 1246 case MAT_NEW_NONZERO_LOCATIONS: 1247 a->nonew = (flg ? 0 : 1); 1248 break; 1249 case MAT_NEW_NONZERO_LOCATION_ERR: 1250 a->nonew = (flg ? -1 : 0); 1251 break; 1252 case MAT_NEW_NONZERO_ALLOCATION_ERR: 1253 a->nonew = (flg ? -2 : 0); 1254 break; 1255 case MAT_UNUSED_NONZERO_LOCATION_ERR: 1256 a->nounused = (flg ? -1 : 0); 1257 break; 1258 case MAT_NEW_DIAGONALS: 1259 case MAT_IGNORE_OFF_PROC_ENTRIES: 1260 case MAT_USE_HASH_TABLE: 1261 ierr = PetscInfo1(A,"Option %s ignored\n",MatOptions[op]);CHKERRQ(ierr); 1262 break; 1263 case MAT_SPD: 1264 case MAT_SYMMETRIC: 1265 case MAT_STRUCTURALLY_SYMMETRIC: 1266 case MAT_HERMITIAN: 1267 case MAT_SYMMETRY_ETERNAL: 1268 /* These options are handled directly by MatSetOption() */ 1269 break; 1270 default: 1271 SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_SUP,"unknown option %d",op); 1272 } 1273 PetscFunctionReturn(0); 1274 } 1275 1276 #undef __FUNCT__ 1277 #define __FUNCT__ "MatGetRow_SeqBAIJ" 1278 PetscErrorCode MatGetRow_SeqBAIJ(Mat A,PetscInt row,PetscInt *nz,PetscInt **idx,PetscScalar **v) 1279 { 1280 Mat_SeqBAIJ *a = (Mat_SeqBAIJ*)A->data; 1281 PetscErrorCode ierr; 1282 PetscInt itmp,i,j,k,M,*ai,*aj,bs,bn,bp,*idx_i,bs2; 1283 MatScalar *aa,*aa_i; 1284 PetscScalar *v_i; 1285 1286 PetscFunctionBegin; 1287 bs = A->rmap->bs; 1288 ai = a->i; 1289 aj = a->j; 1290 aa = a->a; 1291 bs2 = a->bs2; 1292 1293 if (row < 0 || row >= A->rmap->N) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Row %D out of range", row); 1294 1295 bn = row/bs; /* Block number */ 1296 bp = row % bs; /* Block Position */ 1297 M = ai[bn+1] - ai[bn]; 1298 *nz = bs*M; 1299 1300 if (v) { 1301 *v = 0; 1302 if (*nz) { 1303 ierr = PetscMalloc1((*nz),v);CHKERRQ(ierr); 1304 for (i=0; i<M; i++) { /* for each block in the block row */ 1305 v_i = *v + i*bs; 1306 aa_i = aa + bs2*(ai[bn] + i); 1307 for (j=bp,k=0; j<bs2; j+=bs,k++) v_i[k] = aa_i[j]; 1308 } 1309 } 1310 } 1311 1312 if (idx) { 1313 *idx = 0; 1314 if (*nz) { 1315 ierr = PetscMalloc1((*nz),idx);CHKERRQ(ierr); 1316 for (i=0; i<M; i++) { /* for each block in the block row */ 1317 idx_i = *idx + i*bs; 1318 itmp = bs*aj[ai[bn] + i]; 1319 for (j=0; j<bs; j++) idx_i[j] = itmp++; 1320 } 1321 } 1322 } 1323 PetscFunctionReturn(0); 1324 } 1325 1326 #undef __FUNCT__ 1327 #define __FUNCT__ "MatRestoreRow_SeqBAIJ" 1328 PetscErrorCode MatRestoreRow_SeqBAIJ(Mat A,PetscInt row,PetscInt *nz,PetscInt **idx,PetscScalar **v) 1329 { 1330 PetscErrorCode ierr; 1331 1332 PetscFunctionBegin; 1333 if (idx) {ierr = PetscFree(*idx);CHKERRQ(ierr);} 1334 if (v) {ierr = PetscFree(*v);CHKERRQ(ierr);} 1335 PetscFunctionReturn(0); 1336 } 1337 1338 extern PetscErrorCode MatSetValues_SeqBAIJ(Mat,PetscInt,const PetscInt[],PetscInt,const PetscInt[],const PetscScalar[],InsertMode); 1339 1340 #undef __FUNCT__ 1341 #define __FUNCT__ "MatTranspose_SeqBAIJ" 1342 PetscErrorCode MatTranspose_SeqBAIJ(Mat A,MatReuse reuse,Mat *B) 1343 { 1344 Mat_SeqBAIJ *a=(Mat_SeqBAIJ*)A->data; 1345 Mat C; 1346 PetscErrorCode ierr; 1347 PetscInt i,j,k,*aj=a->j,*ai=a->i,bs=A->rmap->bs,mbs=a->mbs,nbs=a->nbs,len,*col; 1348 PetscInt *rows,*cols,bs2=a->bs2; 1349 MatScalar *array; 1350 1351 PetscFunctionBegin; 1352 if (reuse == MAT_REUSE_MATRIX && A == *B && mbs != nbs) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Square matrix only for in-place"); 1353 if (reuse == MAT_INITIAL_MATRIX || A == *B) { 1354 ierr = PetscCalloc1((1+nbs),&col);CHKERRQ(ierr); 1355 1356 for (i=0; i<ai[mbs]; i++) col[aj[i]] += 1; 1357 ierr = MatCreate(PetscObjectComm((PetscObject)A),&C);CHKERRQ(ierr); 1358 ierr = MatSetSizes(C,A->cmap->n,A->rmap->N,A->cmap->n,A->rmap->N);CHKERRQ(ierr); 1359 ierr = MatSetType(C,((PetscObject)A)->type_name);CHKERRQ(ierr); 1360 ierr = MatSeqBAIJSetPreallocation_SeqBAIJ(C,bs,0,col);CHKERRQ(ierr); 1361 ierr = PetscFree(col);CHKERRQ(ierr); 1362 } else { 1363 C = *B; 1364 } 1365 1366 array = a->a; 1367 ierr = PetscMalloc2(bs,&rows,bs,&cols);CHKERRQ(ierr); 1368 for (i=0; i<mbs; i++) { 1369 cols[0] = i*bs; 1370 for (k=1; k<bs; k++) cols[k] = cols[k-1] + 1; 1371 len = ai[i+1] - ai[i]; 1372 for (j=0; j<len; j++) { 1373 rows[0] = (*aj++)*bs; 1374 for (k=1; k<bs; k++) rows[k] = rows[k-1] + 1; 1375 ierr = MatSetValues_SeqBAIJ(C,bs,rows,bs,cols,array,INSERT_VALUES);CHKERRQ(ierr); 1376 array += bs2; 1377 } 1378 } 1379 ierr = PetscFree2(rows,cols);CHKERRQ(ierr); 1380 1381 ierr = MatAssemblyBegin(C,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 1382 ierr = MatAssemblyEnd(C,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 1383 1384 if (reuse == MAT_INITIAL_MATRIX || *B != A) { 1385 *B = C; 1386 } else { 1387 ierr = MatHeaderMerge(A,C);CHKERRQ(ierr); 1388 } 1389 PetscFunctionReturn(0); 1390 } 1391 1392 #undef __FUNCT__ 1393 #define __FUNCT__ "MatIsTranspose_SeqBAIJ" 1394 PetscErrorCode MatIsTranspose_SeqBAIJ(Mat A,Mat B,PetscReal tol,PetscBool *f) 1395 { 1396 PetscErrorCode ierr; 1397 Mat Btrans; 1398 1399 PetscFunctionBegin; 1400 *f = PETSC_FALSE; 1401 ierr = MatTranspose_SeqBAIJ(A,MAT_INITIAL_MATRIX,&Btrans);CHKERRQ(ierr); 1402 ierr = MatEqual_SeqBAIJ(B,Btrans,f);CHKERRQ(ierr); 1403 ierr = MatDestroy(&Btrans);CHKERRQ(ierr); 1404 PetscFunctionReturn(0); 1405 } 1406 1407 #undef __FUNCT__ 1408 #define __FUNCT__ "MatView_SeqBAIJ_Binary" 1409 static PetscErrorCode MatView_SeqBAIJ_Binary(Mat A,PetscViewer viewer) 1410 { 1411 Mat_SeqBAIJ *a = (Mat_SeqBAIJ*)A->data; 1412 PetscErrorCode ierr; 1413 PetscInt i,*col_lens,bs = A->rmap->bs,count,*jj,j,k,l,bs2=a->bs2; 1414 int fd; 1415 PetscScalar *aa; 1416 FILE *file; 1417 1418 PetscFunctionBegin; 1419 ierr = PetscViewerBinaryGetDescriptor(viewer,&fd);CHKERRQ(ierr); 1420 ierr = PetscMalloc1((4+A->rmap->N),&col_lens);CHKERRQ(ierr); 1421 col_lens[0] = MAT_FILE_CLASSID; 1422 1423 col_lens[1] = A->rmap->N; 1424 col_lens[2] = A->cmap->n; 1425 col_lens[3] = a->nz*bs2; 1426 1427 /* store lengths of each row and write (including header) to file */ 1428 count = 0; 1429 for (i=0; i<a->mbs; i++) { 1430 for (j=0; j<bs; j++) { 1431 col_lens[4+count++] = bs*(a->i[i+1] - a->i[i]); 1432 } 1433 } 1434 ierr = PetscBinaryWrite(fd,col_lens,4+A->rmap->N,PETSC_INT,PETSC_TRUE);CHKERRQ(ierr); 1435 ierr = PetscFree(col_lens);CHKERRQ(ierr); 1436 1437 /* store column indices (zero start index) */ 1438 ierr = PetscMalloc1((a->nz+1)*bs2,&jj);CHKERRQ(ierr); 1439 count = 0; 1440 for (i=0; i<a->mbs; i++) { 1441 for (j=0; j<bs; j++) { 1442 for (k=a->i[i]; k<a->i[i+1]; k++) { 1443 for (l=0; l<bs; l++) { 1444 jj[count++] = bs*a->j[k] + l; 1445 } 1446 } 1447 } 1448 } 1449 ierr = PetscBinaryWrite(fd,jj,bs2*a->nz,PETSC_INT,PETSC_FALSE);CHKERRQ(ierr); 1450 ierr = PetscFree(jj);CHKERRQ(ierr); 1451 1452 /* store nonzero values */ 1453 ierr = PetscMalloc1((a->nz+1)*bs2,&aa);CHKERRQ(ierr); 1454 count = 0; 1455 for (i=0; i<a->mbs; i++) { 1456 for (j=0; j<bs; j++) { 1457 for (k=a->i[i]; k<a->i[i+1]; k++) { 1458 for (l=0; l<bs; l++) { 1459 aa[count++] = a->a[bs2*k + l*bs + j]; 1460 } 1461 } 1462 } 1463 } 1464 ierr = PetscBinaryWrite(fd,aa,bs2*a->nz,PETSC_SCALAR,PETSC_FALSE);CHKERRQ(ierr); 1465 ierr = PetscFree(aa);CHKERRQ(ierr); 1466 1467 ierr = PetscViewerBinaryGetInfoPointer(viewer,&file);CHKERRQ(ierr); 1468 if (file) { 1469 fprintf(file,"-matload_block_size %d\n",(int)A->rmap->bs); 1470 } 1471 PetscFunctionReturn(0); 1472 } 1473 1474 #undef __FUNCT__ 1475 #define __FUNCT__ "MatView_SeqBAIJ_ASCII" 1476 static PetscErrorCode MatView_SeqBAIJ_ASCII(Mat A,PetscViewer viewer) 1477 { 1478 Mat_SeqBAIJ *a = (Mat_SeqBAIJ*)A->data; 1479 PetscErrorCode ierr; 1480 PetscInt i,j,bs = A->rmap->bs,k,l,bs2=a->bs2; 1481 PetscViewerFormat format; 1482 1483 PetscFunctionBegin; 1484 ierr = PetscViewerGetFormat(viewer,&format);CHKERRQ(ierr); 1485 if (format == PETSC_VIEWER_ASCII_INFO || format == PETSC_VIEWER_ASCII_INFO_DETAIL) { 1486 ierr = PetscViewerASCIIPrintf(viewer," block size is %D\n",bs);CHKERRQ(ierr); 1487 } else if (format == PETSC_VIEWER_ASCII_MATLAB) { 1488 Mat aij; 1489 ierr = MatConvert(A,MATSEQAIJ,MAT_INITIAL_MATRIX,&aij);CHKERRQ(ierr); 1490 ierr = MatView(aij,viewer);CHKERRQ(ierr); 1491 ierr = MatDestroy(&aij);CHKERRQ(ierr); 1492 } else if (format == PETSC_VIEWER_ASCII_FACTOR_INFO) { 1493 PetscFunctionReturn(0); 1494 } else if (format == PETSC_VIEWER_ASCII_COMMON) { 1495 ierr = PetscViewerASCIIUseTabs(viewer,PETSC_FALSE);CHKERRQ(ierr); 1496 for (i=0; i<a->mbs; i++) { 1497 for (j=0; j<bs; j++) { 1498 ierr = PetscViewerASCIIPrintf(viewer,"row %D:",i*bs+j);CHKERRQ(ierr); 1499 for (k=a->i[i]; k<a->i[i+1]; k++) { 1500 for (l=0; l<bs; l++) { 1501 #if defined(PETSC_USE_COMPLEX) 1502 if (PetscImaginaryPart(a->a[bs2*k + l*bs + j]) > 0.0 && PetscRealPart(a->a[bs2*k + l*bs + j]) != 0.0) { 1503 ierr = PetscViewerASCIIPrintf(viewer," (%D, %g + %gi) ",bs*a->j[k]+l, 1504 (double)PetscRealPart(a->a[bs2*k + l*bs + j]),(double)PetscImaginaryPart(a->a[bs2*k + l*bs + j]));CHKERRQ(ierr); 1505 } else if (PetscImaginaryPart(a->a[bs2*k + l*bs + j]) < 0.0 && PetscRealPart(a->a[bs2*k + l*bs + j]) != 0.0) { 1506 ierr = PetscViewerASCIIPrintf(viewer," (%D, %g - %gi) ",bs*a->j[k]+l, 1507 (double)PetscRealPart(a->a[bs2*k + l*bs + j]),-(double)PetscImaginaryPart(a->a[bs2*k + l*bs + j]));CHKERRQ(ierr); 1508 } else if (PetscRealPart(a->a[bs2*k + l*bs + j]) != 0.0) { 1509 ierr = PetscViewerASCIIPrintf(viewer," (%D, %g) ",bs*a->j[k]+l,(double)PetscRealPart(a->a[bs2*k + l*bs + j]));CHKERRQ(ierr); 1510 } 1511 #else 1512 if (a->a[bs2*k + l*bs + j] != 0.0) { 1513 ierr = PetscViewerASCIIPrintf(viewer," (%D, %g) ",bs*a->j[k]+l,(double)a->a[bs2*k + l*bs + j]);CHKERRQ(ierr); 1514 } 1515 #endif 1516 } 1517 } 1518 ierr = PetscViewerASCIIPrintf(viewer,"\n");CHKERRQ(ierr); 1519 } 1520 } 1521 ierr = PetscViewerASCIIUseTabs(viewer,PETSC_TRUE);CHKERRQ(ierr); 1522 } else { 1523 ierr = PetscViewerASCIIUseTabs(viewer,PETSC_FALSE);CHKERRQ(ierr); 1524 for (i=0; i<a->mbs; i++) { 1525 for (j=0; j<bs; j++) { 1526 ierr = PetscViewerASCIIPrintf(viewer,"row %D:",i*bs+j);CHKERRQ(ierr); 1527 for (k=a->i[i]; k<a->i[i+1]; k++) { 1528 for (l=0; l<bs; l++) { 1529 #if defined(PETSC_USE_COMPLEX) 1530 if (PetscImaginaryPart(a->a[bs2*k + l*bs + j]) > 0.0) { 1531 ierr = PetscViewerASCIIPrintf(viewer," (%D, %g + %g i) ",bs*a->j[k]+l, 1532 (double)PetscRealPart(a->a[bs2*k + l*bs + j]),(double)PetscImaginaryPart(a->a[bs2*k + l*bs + j]));CHKERRQ(ierr); 1533 } else if (PetscImaginaryPart(a->a[bs2*k + l*bs + j]) < 0.0) { 1534 ierr = PetscViewerASCIIPrintf(viewer," (%D, %g - %g i) ",bs*a->j[k]+l, 1535 (double)PetscRealPart(a->a[bs2*k + l*bs + j]),-(double)PetscImaginaryPart(a->a[bs2*k + l*bs + j]));CHKERRQ(ierr); 1536 } else { 1537 ierr = PetscViewerASCIIPrintf(viewer," (%D, %g) ",bs*a->j[k]+l,(double)PetscRealPart(a->a[bs2*k + l*bs + j]));CHKERRQ(ierr); 1538 } 1539 #else 1540 ierr = PetscViewerASCIIPrintf(viewer," (%D, %g) ",bs*a->j[k]+l,(double)a->a[bs2*k + l*bs + j]);CHKERRQ(ierr); 1541 #endif 1542 } 1543 } 1544 ierr = PetscViewerASCIIPrintf(viewer,"\n");CHKERRQ(ierr); 1545 } 1546 } 1547 ierr = PetscViewerASCIIUseTabs(viewer,PETSC_TRUE);CHKERRQ(ierr); 1548 } 1549 ierr = PetscViewerFlush(viewer);CHKERRQ(ierr); 1550 PetscFunctionReturn(0); 1551 } 1552 1553 #include <petscdraw.h> 1554 #undef __FUNCT__ 1555 #define __FUNCT__ "MatView_SeqBAIJ_Draw_Zoom" 1556 static PetscErrorCode MatView_SeqBAIJ_Draw_Zoom(PetscDraw draw,void *Aa) 1557 { 1558 Mat A = (Mat) Aa; 1559 Mat_SeqBAIJ *a=(Mat_SeqBAIJ*)A->data; 1560 PetscErrorCode ierr; 1561 PetscInt row,i,j,k,l,mbs=a->mbs,color,bs=A->rmap->bs,bs2=a->bs2; 1562 PetscReal xl,yl,xr,yr,x_l,x_r,y_l,y_r; 1563 MatScalar *aa; 1564 PetscViewer viewer; 1565 PetscViewerFormat format; 1566 1567 PetscFunctionBegin; 1568 ierr = PetscObjectQuery((PetscObject)A,"Zoomviewer",(PetscObject*)&viewer);CHKERRQ(ierr); 1569 ierr = PetscViewerGetFormat(viewer,&format);CHKERRQ(ierr); 1570 1571 ierr = PetscDrawGetCoordinates(draw,&xl,&yl,&xr,&yr);CHKERRQ(ierr); 1572 1573 /* loop over matrix elements drawing boxes */ 1574 1575 if (format != PETSC_VIEWER_DRAW_CONTOUR) { 1576 color = PETSC_DRAW_BLUE; 1577 for (i=0,row=0; i<mbs; i++,row+=bs) { 1578 for (j=a->i[i]; j<a->i[i+1]; j++) { 1579 y_l = A->rmap->N - row - 1.0; y_r = y_l + 1.0; 1580 x_l = a->j[j]*bs; x_r = x_l + 1.0; 1581 aa = a->a + j*bs2; 1582 for (k=0; k<bs; k++) { 1583 for (l=0; l<bs; l++) { 1584 if (PetscRealPart(*aa++) >= 0.) continue; 1585 ierr = PetscDrawRectangle(draw,x_l+k,y_l-l,x_r+k,y_r-l,color,color,color,color);CHKERRQ(ierr); 1586 } 1587 } 1588 } 1589 } 1590 color = PETSC_DRAW_CYAN; 1591 for (i=0,row=0; i<mbs; i++,row+=bs) { 1592 for (j=a->i[i]; j<a->i[i+1]; j++) { 1593 y_l = A->rmap->N - row - 1.0; y_r = y_l + 1.0; 1594 x_l = a->j[j]*bs; x_r = x_l + 1.0; 1595 aa = a->a + j*bs2; 1596 for (k=0; k<bs; k++) { 1597 for (l=0; l<bs; l++) { 1598 if (PetscRealPart(*aa++) != 0.) continue; 1599 ierr = PetscDrawRectangle(draw,x_l+k,y_l-l,x_r+k,y_r-l,color,color,color,color);CHKERRQ(ierr); 1600 } 1601 } 1602 } 1603 } 1604 color = PETSC_DRAW_RED; 1605 for (i=0,row=0; i<mbs; i++,row+=bs) { 1606 for (j=a->i[i]; j<a->i[i+1]; j++) { 1607 y_l = A->rmap->N - row - 1.0; y_r = y_l + 1.0; 1608 x_l = a->j[j]*bs; x_r = x_l + 1.0; 1609 aa = a->a + j*bs2; 1610 for (k=0; k<bs; k++) { 1611 for (l=0; l<bs; l++) { 1612 if (PetscRealPart(*aa++) <= 0.) continue; 1613 ierr = PetscDrawRectangle(draw,x_l+k,y_l-l,x_r+k,y_r-l,color,color,color,color);CHKERRQ(ierr); 1614 } 1615 } 1616 } 1617 } 1618 } else { 1619 /* use contour shading to indicate magnitude of values */ 1620 /* first determine max of all nonzero values */ 1621 PetscDraw popup; 1622 PetscReal scale,maxv = 0.0; 1623 1624 for (i=0; i<a->nz*a->bs2; i++) { 1625 if (PetscAbsScalar(a->a[i]) > maxv) maxv = PetscAbsScalar(a->a[i]); 1626 } 1627 scale = (245.0 - PETSC_DRAW_BASIC_COLORS)/maxv; 1628 ierr = PetscDrawGetPopup(draw,&popup);CHKERRQ(ierr); 1629 if (popup) { 1630 ierr = PetscDrawScalePopup(popup,0.0,maxv);CHKERRQ(ierr); 1631 } 1632 for (i=0,row=0; i<mbs; i++,row+=bs) { 1633 for (j=a->i[i]; j<a->i[i+1]; j++) { 1634 y_l = A->rmap->N - row - 1.0; y_r = y_l + 1.0; 1635 x_l = a->j[j]*bs; x_r = x_l + 1.0; 1636 aa = a->a + j*bs2; 1637 for (k=0; k<bs; k++) { 1638 for (l=0; l<bs; l++) { 1639 color = PETSC_DRAW_BASIC_COLORS + (PetscInt)(scale*PetscAbsScalar(*aa++)); 1640 ierr = PetscDrawRectangle(draw,x_l+k,y_l-l,x_r+k,y_r-l,color,color,color,color);CHKERRQ(ierr); 1641 } 1642 } 1643 } 1644 } 1645 } 1646 PetscFunctionReturn(0); 1647 } 1648 1649 #undef __FUNCT__ 1650 #define __FUNCT__ "MatView_SeqBAIJ_Draw" 1651 static PetscErrorCode MatView_SeqBAIJ_Draw(Mat A,PetscViewer viewer) 1652 { 1653 PetscErrorCode ierr; 1654 PetscReal xl,yl,xr,yr,w,h; 1655 PetscDraw draw; 1656 PetscBool isnull; 1657 1658 PetscFunctionBegin; 1659 ierr = PetscViewerDrawGetDraw(viewer,0,&draw);CHKERRQ(ierr); 1660 ierr = PetscDrawIsNull(draw,&isnull);CHKERRQ(ierr); if (isnull) PetscFunctionReturn(0); 1661 1662 ierr = PetscObjectCompose((PetscObject)A,"Zoomviewer",(PetscObject)viewer);CHKERRQ(ierr); 1663 xr = A->cmap->n; yr = A->rmap->N; h = yr/10.0; w = xr/10.0; 1664 xr += w; yr += h; xl = -w; yl = -h; 1665 ierr = PetscDrawSetCoordinates(draw,xl,yl,xr,yr);CHKERRQ(ierr); 1666 ierr = PetscDrawZoom(draw,MatView_SeqBAIJ_Draw_Zoom,A);CHKERRQ(ierr); 1667 ierr = PetscObjectCompose((PetscObject)A,"Zoomviewer",NULL);CHKERRQ(ierr); 1668 PetscFunctionReturn(0); 1669 } 1670 1671 #undef __FUNCT__ 1672 #define __FUNCT__ "MatView_SeqBAIJ" 1673 PetscErrorCode MatView_SeqBAIJ(Mat A,PetscViewer viewer) 1674 { 1675 PetscErrorCode ierr; 1676 PetscBool iascii,isbinary,isdraw; 1677 1678 PetscFunctionBegin; 1679 ierr = PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERASCII,&iascii);CHKERRQ(ierr); 1680 ierr = PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERBINARY,&isbinary);CHKERRQ(ierr); 1681 ierr = PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERDRAW,&isdraw);CHKERRQ(ierr); 1682 if (iascii) { 1683 ierr = MatView_SeqBAIJ_ASCII(A,viewer);CHKERRQ(ierr); 1684 } else if (isbinary) { 1685 ierr = MatView_SeqBAIJ_Binary(A,viewer);CHKERRQ(ierr); 1686 } else if (isdraw) { 1687 ierr = MatView_SeqBAIJ_Draw(A,viewer);CHKERRQ(ierr); 1688 } else { 1689 Mat B; 1690 ierr = MatConvert(A,MATSEQAIJ,MAT_INITIAL_MATRIX,&B);CHKERRQ(ierr); 1691 ierr = MatView(B,viewer);CHKERRQ(ierr); 1692 ierr = MatDestroy(&B);CHKERRQ(ierr); 1693 } 1694 PetscFunctionReturn(0); 1695 } 1696 1697 1698 #undef __FUNCT__ 1699 #define __FUNCT__ "MatGetValues_SeqBAIJ" 1700 PetscErrorCode MatGetValues_SeqBAIJ(Mat A,PetscInt m,const PetscInt im[],PetscInt n,const PetscInt in[],PetscScalar v[]) 1701 { 1702 Mat_SeqBAIJ *a = (Mat_SeqBAIJ*)A->data; 1703 PetscInt *rp,k,low,high,t,row,nrow,i,col,l,*aj = a->j; 1704 PetscInt *ai = a->i,*ailen = a->ilen; 1705 PetscInt brow,bcol,ridx,cidx,bs=A->rmap->bs,bs2=a->bs2; 1706 MatScalar *ap,*aa = a->a; 1707 1708 PetscFunctionBegin; 1709 for (k=0; k<m; k++) { /* loop over rows */ 1710 row = im[k]; brow = row/bs; 1711 if (row < 0) {v += n; continue;} /* SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Negative row"); */ 1712 if (row >= A->rmap->N) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Row %D too large", row); 1713 rp = aj + ai[brow]; ap = aa + bs2*ai[brow]; 1714 nrow = ailen[brow]; 1715 for (l=0; l<n; l++) { /* loop over columns */ 1716 if (in[l] < 0) {v++; continue;} /* SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Negative column"); */ 1717 if (in[l] >= A->cmap->n) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Column %D too large", in[l]); 1718 col = in[l]; 1719 bcol = col/bs; 1720 cidx = col%bs; 1721 ridx = row%bs; 1722 high = nrow; 1723 low = 0; /* assume unsorted */ 1724 while (high-low > 5) { 1725 t = (low+high)/2; 1726 if (rp[t] > bcol) high = t; 1727 else low = t; 1728 } 1729 for (i=low; i<high; i++) { 1730 if (rp[i] > bcol) break; 1731 if (rp[i] == bcol) { 1732 *v++ = ap[bs2*i+bs*cidx+ridx]; 1733 goto finished; 1734 } 1735 } 1736 *v++ = 0.0; 1737 finished:; 1738 } 1739 } 1740 PetscFunctionReturn(0); 1741 } 1742 1743 #undef __FUNCT__ 1744 #define __FUNCT__ "MatSetValuesBlocked_SeqBAIJ" 1745 PetscErrorCode MatSetValuesBlocked_SeqBAIJ(Mat A,PetscInt m,const PetscInt im[],PetscInt n,const PetscInt in[],const PetscScalar v[],InsertMode is) 1746 { 1747 Mat_SeqBAIJ *a = (Mat_SeqBAIJ*)A->data; 1748 PetscInt *rp,k,low,high,t,ii,jj,row,nrow,i,col,l,rmax,N,lastcol = -1; 1749 PetscInt *imax=a->imax,*ai=a->i,*ailen=a->ilen; 1750 PetscErrorCode ierr; 1751 PetscInt *aj =a->j,nonew=a->nonew,bs2=a->bs2,bs=A->rmap->bs,stepval; 1752 PetscBool roworiented=a->roworiented; 1753 const PetscScalar *value = v; 1754 MatScalar *ap,*aa = a->a,*bap; 1755 1756 PetscFunctionBegin; 1757 if (roworiented) { 1758 stepval = (n-1)*bs; 1759 } else { 1760 stepval = (m-1)*bs; 1761 } 1762 for (k=0; k<m; k++) { /* loop over added rows */ 1763 row = im[k]; 1764 if (row < 0) continue; 1765 #if defined(PETSC_USE_DEBUG) 1766 if (row >= a->mbs) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Row too large: row %D max %D",row,a->mbs-1); 1767 #endif 1768 rp = aj + ai[row]; 1769 ap = aa + bs2*ai[row]; 1770 rmax = imax[row]; 1771 nrow = ailen[row]; 1772 low = 0; 1773 high = nrow; 1774 for (l=0; l<n; l++) { /* loop over added columns */ 1775 if (in[l] < 0) continue; 1776 #if defined(PETSC_USE_DEBUG) 1777 if (in[l] >= a->nbs) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Column too large: col %D max %D",in[l],a->nbs-1); 1778 #endif 1779 col = in[l]; 1780 if (roworiented) { 1781 value = v + (k*(stepval+bs) + l)*bs; 1782 } else { 1783 value = v + (l*(stepval+bs) + k)*bs; 1784 } 1785 if (col <= lastcol) low = 0; 1786 else high = nrow; 1787 lastcol = col; 1788 while (high-low > 7) { 1789 t = (low+high)/2; 1790 if (rp[t] > col) high = t; 1791 else low = t; 1792 } 1793 for (i=low; i<high; i++) { 1794 if (rp[i] > col) break; 1795 if (rp[i] == col) { 1796 bap = ap + bs2*i; 1797 if (roworiented) { 1798 if (is == ADD_VALUES) { 1799 for (ii=0; ii<bs; ii++,value+=stepval) { 1800 for (jj=ii; jj<bs2; jj+=bs) { 1801 bap[jj] += *value++; 1802 } 1803 } 1804 } else { 1805 for (ii=0; ii<bs; ii++,value+=stepval) { 1806 for (jj=ii; jj<bs2; jj+=bs) { 1807 bap[jj] = *value++; 1808 } 1809 } 1810 } 1811 } else { 1812 if (is == ADD_VALUES) { 1813 for (ii=0; ii<bs; ii++,value+=bs+stepval) { 1814 for (jj=0; jj<bs; jj++) { 1815 bap[jj] += value[jj]; 1816 } 1817 bap += bs; 1818 } 1819 } else { 1820 for (ii=0; ii<bs; ii++,value+=bs+stepval) { 1821 for (jj=0; jj<bs; jj++) { 1822 bap[jj] = value[jj]; 1823 } 1824 bap += bs; 1825 } 1826 } 1827 } 1828 goto noinsert2; 1829 } 1830 } 1831 if (nonew == 1) goto noinsert2; 1832 if (nonew == -1) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Inserting a new nonzero (%D, %D) in the matrix", row, col); 1833 MatSeqXAIJReallocateAIJ(A,a->mbs,bs2,nrow,row,col,rmax,aa,ai,aj,rp,ap,imax,nonew,MatScalar); 1834 N = nrow++ - 1; high++; 1835 /* shift up all the later entries in this row */ 1836 for (ii=N; ii>=i; ii--) { 1837 rp[ii+1] = rp[ii]; 1838 ierr = PetscMemcpy(ap+bs2*(ii+1),ap+bs2*(ii),bs2*sizeof(MatScalar));CHKERRQ(ierr); 1839 } 1840 if (N >= i) { 1841 ierr = PetscMemzero(ap+bs2*i,bs2*sizeof(MatScalar));CHKERRQ(ierr); 1842 } 1843 rp[i] = col; 1844 bap = ap + bs2*i; 1845 if (roworiented) { 1846 for (ii=0; ii<bs; ii++,value+=stepval) { 1847 for (jj=ii; jj<bs2; jj+=bs) { 1848 bap[jj] = *value++; 1849 } 1850 } 1851 } else { 1852 for (ii=0; ii<bs; ii++,value+=stepval) { 1853 for (jj=0; jj<bs; jj++) { 1854 *bap++ = *value++; 1855 } 1856 } 1857 } 1858 noinsert2:; 1859 low = i; 1860 } 1861 ailen[row] = nrow; 1862 } 1863 PetscFunctionReturn(0); 1864 } 1865 1866 #undef __FUNCT__ 1867 #define __FUNCT__ "MatAssemblyEnd_SeqBAIJ" 1868 PetscErrorCode MatAssemblyEnd_SeqBAIJ(Mat A,MatAssemblyType mode) 1869 { 1870 Mat_SeqBAIJ *a = (Mat_SeqBAIJ*)A->data; 1871 PetscInt fshift = 0,i,j,*ai = a->i,*aj = a->j,*imax = a->imax; 1872 PetscInt m = A->rmap->N,*ip,N,*ailen = a->ilen; 1873 PetscErrorCode ierr; 1874 PetscInt mbs = a->mbs,bs2 = a->bs2,rmax = 0; 1875 MatScalar *aa = a->a,*ap; 1876 PetscReal ratio=0.6; 1877 1878 PetscFunctionBegin; 1879 if (mode == MAT_FLUSH_ASSEMBLY) PetscFunctionReturn(0); 1880 1881 if (m) rmax = ailen[0]; 1882 for (i=1; i<mbs; i++) { 1883 /* move each row back by the amount of empty slots (fshift) before it*/ 1884 fshift += imax[i-1] - ailen[i-1]; 1885 rmax = PetscMax(rmax,ailen[i]); 1886 if (fshift) { 1887 ip = aj + ai[i]; ap = aa + bs2*ai[i]; 1888 N = ailen[i]; 1889 for (j=0; j<N; j++) { 1890 ip[j-fshift] = ip[j]; 1891 1892 ierr = PetscMemcpy(ap+(j-fshift)*bs2,ap+j*bs2,bs2*sizeof(MatScalar));CHKERRQ(ierr); 1893 } 1894 } 1895 ai[i] = ai[i-1] + ailen[i-1]; 1896 } 1897 if (mbs) { 1898 fshift += imax[mbs-1] - ailen[mbs-1]; 1899 ai[mbs] = ai[mbs-1] + ailen[mbs-1]; 1900 } 1901 1902 /* reset ilen and imax for each row */ 1903 a->nonzerorowcnt = 0; 1904 for (i=0; i<mbs; i++) { 1905 ailen[i] = imax[i] = ai[i+1] - ai[i]; 1906 a->nonzerorowcnt += ((ai[i+1] - ai[i]) > 0); 1907 } 1908 a->nz = ai[mbs]; 1909 1910 /* diagonals may have moved, so kill the diagonal pointers */ 1911 a->idiagvalid = PETSC_FALSE; 1912 if (fshift && a->diag) { 1913 ierr = PetscFree(a->diag);CHKERRQ(ierr); 1914 ierr = PetscLogObjectMemory((PetscObject)A,-(mbs+1)*sizeof(PetscInt));CHKERRQ(ierr); 1915 a->diag = 0; 1916 } 1917 if (fshift && a->nounused == -1) SETERRQ4(PETSC_COMM_SELF,PETSC_ERR_PLIB, "Unused space detected in matrix: %D X %D block size %D, %D unneeded", m, A->cmap->n, A->rmap->bs, fshift*bs2); 1918 ierr = PetscInfo5(A,"Matrix size: %D X %D, block size %D; storage space: %D unneeded, %D used\n",m,A->cmap->n,A->rmap->bs,fshift*bs2,a->nz*bs2);CHKERRQ(ierr); 1919 ierr = PetscInfo1(A,"Number of mallocs during MatSetValues is %D\n",a->reallocs);CHKERRQ(ierr); 1920 ierr = PetscInfo1(A,"Most nonzeros blocks in any row is %D\n",rmax);CHKERRQ(ierr); 1921 1922 A->info.mallocs += a->reallocs; 1923 a->reallocs = 0; 1924 A->info.nz_unneeded = (PetscReal)fshift*bs2; 1925 1926 ierr = MatCheckCompressedRow(A,a->nonzerorowcnt,&a->compressedrow,a->i,mbs,ratio);CHKERRQ(ierr); 1927 PetscFunctionReturn(0); 1928 } 1929 1930 /* 1931 This function returns an array of flags which indicate the locations of contiguous 1932 blocks that should be zeroed. for eg: if bs = 3 and is = [0,1,2,3,5,6,7,8,9] 1933 then the resulting sizes = [3,1,1,3,1] correspondig to sets [(0,1,2),(3),(5),(6,7,8),(9)] 1934 Assume: sizes should be long enough to hold all the values. 1935 */ 1936 #undef __FUNCT__ 1937 #define __FUNCT__ "MatZeroRows_SeqBAIJ_Check_Blocks" 1938 static PetscErrorCode MatZeroRows_SeqBAIJ_Check_Blocks(PetscInt idx[],PetscInt n,PetscInt bs,PetscInt sizes[], PetscInt *bs_max) 1939 { 1940 PetscInt i,j,k,row; 1941 PetscBool flg; 1942 1943 PetscFunctionBegin; 1944 for (i=0,j=0; i<n; j++) { 1945 row = idx[i]; 1946 if (row%bs!=0) { /* Not the begining of a block */ 1947 sizes[j] = 1; 1948 i++; 1949 } else if (i+bs > n) { /* complete block doesn't exist (at idx end) */ 1950 sizes[j] = 1; /* Also makes sure atleast 'bs' values exist for next else */ 1951 i++; 1952 } else { /* Begining of the block, so check if the complete block exists */ 1953 flg = PETSC_TRUE; 1954 for (k=1; k<bs; k++) { 1955 if (row+k != idx[i+k]) { /* break in the block */ 1956 flg = PETSC_FALSE; 1957 break; 1958 } 1959 } 1960 if (flg) { /* No break in the bs */ 1961 sizes[j] = bs; 1962 i += bs; 1963 } else { 1964 sizes[j] = 1; 1965 i++; 1966 } 1967 } 1968 } 1969 *bs_max = j; 1970 PetscFunctionReturn(0); 1971 } 1972 1973 #undef __FUNCT__ 1974 #define __FUNCT__ "MatZeroRows_SeqBAIJ" 1975 PetscErrorCode MatZeroRows_SeqBAIJ(Mat A,PetscInt is_n,const PetscInt is_idx[],PetscScalar diag,Vec x, Vec b) 1976 { 1977 Mat_SeqBAIJ *baij=(Mat_SeqBAIJ*)A->data; 1978 PetscErrorCode ierr; 1979 PetscInt i,j,k,count,*rows; 1980 PetscInt bs=A->rmap->bs,bs2=baij->bs2,*sizes,row,bs_max; 1981 PetscScalar zero = 0.0; 1982 MatScalar *aa; 1983 const PetscScalar *xx; 1984 PetscScalar *bb; 1985 1986 PetscFunctionBegin; 1987 /* fix right hand side if needed */ 1988 if (x && b) { 1989 ierr = VecGetArrayRead(x,&xx);CHKERRQ(ierr); 1990 ierr = VecGetArray(b,&bb);CHKERRQ(ierr); 1991 for (i=0; i<is_n; i++) { 1992 bb[is_idx[i]] = diag*xx[is_idx[i]]; 1993 } 1994 ierr = VecRestoreArrayRead(x,&xx);CHKERRQ(ierr); 1995 ierr = VecRestoreArray(b,&bb);CHKERRQ(ierr); 1996 } 1997 1998 /* Make a copy of the IS and sort it */ 1999 /* allocate memory for rows,sizes */ 2000 ierr = PetscMalloc2(is_n,&rows,2*is_n,&sizes);CHKERRQ(ierr); 2001 2002 /* copy IS values to rows, and sort them */ 2003 for (i=0; i<is_n; i++) rows[i] = is_idx[i]; 2004 ierr = PetscSortInt(is_n,rows);CHKERRQ(ierr); 2005 2006 if (baij->keepnonzeropattern) { 2007 for (i=0; i<is_n; i++) sizes[i] = 1; 2008 bs_max = is_n; 2009 } else { 2010 ierr = MatZeroRows_SeqBAIJ_Check_Blocks(rows,is_n,bs,sizes,&bs_max);CHKERRQ(ierr); 2011 A->nonzerostate++; 2012 } 2013 2014 for (i=0,j=0; i<bs_max; j+=sizes[i],i++) { 2015 row = rows[j]; 2016 if (row < 0 || row > A->rmap->N) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"row %D out of range",row); 2017 count = (baij->i[row/bs +1] - baij->i[row/bs])*bs; 2018 aa = ((MatScalar*)(baij->a)) + baij->i[row/bs]*bs2 + (row%bs); 2019 if (sizes[i] == bs && !baij->keepnonzeropattern) { 2020 if (diag != (PetscScalar)0.0) { 2021 if (baij->ilen[row/bs] > 0) { 2022 baij->ilen[row/bs] = 1; 2023 baij->j[baij->i[row/bs]] = row/bs; 2024 2025 ierr = PetscMemzero(aa,count*bs*sizeof(MatScalar));CHKERRQ(ierr); 2026 } 2027 /* Now insert all the diagonal values for this bs */ 2028 for (k=0; k<bs; k++) { 2029 ierr = (*A->ops->setvalues)(A,1,rows+j+k,1,rows+j+k,&diag,INSERT_VALUES);CHKERRQ(ierr); 2030 } 2031 } else { /* (diag == 0.0) */ 2032 baij->ilen[row/bs] = 0; 2033 } /* end (diag == 0.0) */ 2034 } else { /* (sizes[i] != bs) */ 2035 #if defined(PETSC_USE_DEBUG) 2036 if (sizes[i] != 1) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_PLIB,"Internal Error. Value should be 1"); 2037 #endif 2038 for (k=0; k<count; k++) { 2039 aa[0] = zero; 2040 aa += bs; 2041 } 2042 if (diag != (PetscScalar)0.0) { 2043 ierr = (*A->ops->setvalues)(A,1,rows+j,1,rows+j,&diag,INSERT_VALUES);CHKERRQ(ierr); 2044 } 2045 } 2046 } 2047 2048 ierr = PetscFree2(rows,sizes);CHKERRQ(ierr); 2049 ierr = MatAssemblyEnd_SeqBAIJ(A,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 2050 PetscFunctionReturn(0); 2051 } 2052 2053 #undef __FUNCT__ 2054 #define __FUNCT__ "MatZeroRowsColumns_SeqBAIJ" 2055 PetscErrorCode MatZeroRowsColumns_SeqBAIJ(Mat A,PetscInt is_n,const PetscInt is_idx[],PetscScalar diag,Vec x, Vec b) 2056 { 2057 Mat_SeqBAIJ *baij=(Mat_SeqBAIJ*)A->data; 2058 PetscErrorCode ierr; 2059 PetscInt i,j,k,count; 2060 PetscInt bs =A->rmap->bs,bs2=baij->bs2,row,col; 2061 PetscScalar zero = 0.0; 2062 MatScalar *aa; 2063 const PetscScalar *xx; 2064 PetscScalar *bb; 2065 PetscBool *zeroed,vecs = PETSC_FALSE; 2066 2067 PetscFunctionBegin; 2068 /* fix right hand side if needed */ 2069 if (x && b) { 2070 ierr = VecGetArrayRead(x,&xx);CHKERRQ(ierr); 2071 ierr = VecGetArray(b,&bb);CHKERRQ(ierr); 2072 vecs = PETSC_TRUE; 2073 } 2074 2075 /* zero the columns */ 2076 ierr = PetscCalloc1(A->rmap->n,&zeroed);CHKERRQ(ierr); 2077 for (i=0; i<is_n; i++) { 2078 if (is_idx[i] < 0 || is_idx[i] >= A->rmap->N) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"row %D out of range",is_idx[i]); 2079 zeroed[is_idx[i]] = PETSC_TRUE; 2080 } 2081 for (i=0; i<A->rmap->N; i++) { 2082 if (!zeroed[i]) { 2083 row = i/bs; 2084 for (j=baij->i[row]; j<baij->i[row+1]; j++) { 2085 for (k=0; k<bs; k++) { 2086 col = bs*baij->j[j] + k; 2087 if (zeroed[col]) { 2088 aa = ((MatScalar*)(baij->a)) + j*bs2 + (i%bs) + bs*k; 2089 if (vecs) bb[i] -= aa[0]*xx[col]; 2090 aa[0] = 0.0; 2091 } 2092 } 2093 } 2094 } else if (vecs) bb[i] = diag*xx[i]; 2095 } 2096 ierr = PetscFree(zeroed);CHKERRQ(ierr); 2097 if (vecs) { 2098 ierr = VecRestoreArrayRead(x,&xx);CHKERRQ(ierr); 2099 ierr = VecRestoreArray(b,&bb);CHKERRQ(ierr); 2100 } 2101 2102 /* zero the rows */ 2103 for (i=0; i<is_n; i++) { 2104 row = is_idx[i]; 2105 count = (baij->i[row/bs +1] - baij->i[row/bs])*bs; 2106 aa = ((MatScalar*)(baij->a)) + baij->i[row/bs]*bs2 + (row%bs); 2107 for (k=0; k<count; k++) { 2108 aa[0] = zero; 2109 aa += bs; 2110 } 2111 if (diag != (PetscScalar)0.0) { 2112 ierr = (*A->ops->setvalues)(A,1,&row,1,&row,&diag,INSERT_VALUES);CHKERRQ(ierr); 2113 } 2114 } 2115 ierr = MatAssemblyEnd_SeqBAIJ(A,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 2116 PetscFunctionReturn(0); 2117 } 2118 2119 #undef __FUNCT__ 2120 #define __FUNCT__ "MatSetValues_SeqBAIJ" 2121 PetscErrorCode MatSetValues_SeqBAIJ(Mat A,PetscInt m,const PetscInt im[],PetscInt n,const PetscInt in[],const PetscScalar v[],InsertMode is) 2122 { 2123 Mat_SeqBAIJ *a = (Mat_SeqBAIJ*)A->data; 2124 PetscInt *rp,k,low,high,t,ii,row,nrow,i,col,l,rmax,N,lastcol = -1; 2125 PetscInt *imax=a->imax,*ai=a->i,*ailen=a->ilen; 2126 PetscInt *aj =a->j,nonew=a->nonew,bs=A->rmap->bs,brow,bcol; 2127 PetscErrorCode ierr; 2128 PetscInt ridx,cidx,bs2=a->bs2; 2129 PetscBool roworiented=a->roworiented; 2130 MatScalar *ap,value,*aa=a->a,*bap; 2131 2132 PetscFunctionBegin; 2133 for (k=0; k<m; k++) { /* loop over added rows */ 2134 row = im[k]; 2135 brow = row/bs; 2136 if (row < 0) continue; 2137 #if defined(PETSC_USE_DEBUG) 2138 if (row >= A->rmap->N) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Row too large: row %D max %D",row,A->rmap->N-1); 2139 #endif 2140 rp = aj + ai[brow]; 2141 ap = aa + bs2*ai[brow]; 2142 rmax = imax[brow]; 2143 nrow = ailen[brow]; 2144 low = 0; 2145 high = nrow; 2146 for (l=0; l<n; l++) { /* loop over added columns */ 2147 if (in[l] < 0) continue; 2148 #if defined(PETSC_USE_DEBUG) 2149 if (in[l] >= A->cmap->n) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Column too large: col %D max %D",in[l],A->cmap->n-1); 2150 #endif 2151 col = in[l]; bcol = col/bs; 2152 ridx = row % bs; cidx = col % bs; 2153 if (roworiented) { 2154 value = v[l + k*n]; 2155 } else { 2156 value = v[k + l*m]; 2157 } 2158 if (col <= lastcol) low = 0; else high = nrow; 2159 lastcol = col; 2160 while (high-low > 7) { 2161 t = (low+high)/2; 2162 if (rp[t] > bcol) high = t; 2163 else low = t; 2164 } 2165 for (i=low; i<high; i++) { 2166 if (rp[i] > bcol) break; 2167 if (rp[i] == bcol) { 2168 bap = ap + bs2*i + bs*cidx + ridx; 2169 if (is == ADD_VALUES) *bap += value; 2170 else *bap = value; 2171 goto noinsert1; 2172 } 2173 } 2174 if (nonew == 1) goto noinsert1; 2175 if (nonew == -1) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Inserting a new nonzero (%D, %D) in the matrix", row, col); 2176 MatSeqXAIJReallocateAIJ(A,a->mbs,bs2,nrow,brow,bcol,rmax,aa,ai,aj,rp,ap,imax,nonew,MatScalar); 2177 N = nrow++ - 1; high++; 2178 /* shift up all the later entries in this row */ 2179 for (ii=N; ii>=i; ii--) { 2180 rp[ii+1] = rp[ii]; 2181 ierr = PetscMemcpy(ap+bs2*(ii+1),ap+bs2*(ii),bs2*sizeof(MatScalar));CHKERRQ(ierr); 2182 } 2183 if (N>=i) { 2184 ierr = PetscMemzero(ap+bs2*i,bs2*sizeof(MatScalar));CHKERRQ(ierr); 2185 } 2186 rp[i] = bcol; 2187 ap[bs2*i + bs*cidx + ridx] = value; 2188 a->nz++; 2189 A->nonzerostate++; 2190 noinsert1:; 2191 low = i; 2192 } 2193 ailen[brow] = nrow; 2194 } 2195 PetscFunctionReturn(0); 2196 } 2197 2198 #undef __FUNCT__ 2199 #define __FUNCT__ "MatILUFactor_SeqBAIJ" 2200 PetscErrorCode MatILUFactor_SeqBAIJ(Mat inA,IS row,IS col,const MatFactorInfo *info) 2201 { 2202 Mat_SeqBAIJ *a = (Mat_SeqBAIJ*)inA->data; 2203 Mat outA; 2204 PetscErrorCode ierr; 2205 PetscBool row_identity,col_identity; 2206 2207 PetscFunctionBegin; 2208 if (info->levels != 0) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"Only levels = 0 supported for in-place ILU"); 2209 ierr = ISIdentity(row,&row_identity);CHKERRQ(ierr); 2210 ierr = ISIdentity(col,&col_identity);CHKERRQ(ierr); 2211 if (!row_identity || !col_identity) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONG,"Row and column permutations must be identity for in-place ILU"); 2212 2213 outA = inA; 2214 inA->factortype = MAT_FACTOR_LU; 2215 2216 ierr = MatMarkDiagonal_SeqBAIJ(inA);CHKERRQ(ierr); 2217 2218 ierr = PetscObjectReference((PetscObject)row);CHKERRQ(ierr); 2219 ierr = ISDestroy(&a->row);CHKERRQ(ierr); 2220 a->row = row; 2221 ierr = PetscObjectReference((PetscObject)col);CHKERRQ(ierr); 2222 ierr = ISDestroy(&a->col);CHKERRQ(ierr); 2223 a->col = col; 2224 2225 /* Create the invert permutation so that it can be used in MatLUFactorNumeric() */ 2226 ierr = ISDestroy(&a->icol);CHKERRQ(ierr); 2227 ierr = ISInvertPermutation(col,PETSC_DECIDE,&a->icol);CHKERRQ(ierr); 2228 ierr = PetscLogObjectParent((PetscObject)inA,(PetscObject)a->icol);CHKERRQ(ierr); 2229 2230 ierr = MatSeqBAIJSetNumericFactorization_inplace(inA,(PetscBool)(row_identity && col_identity));CHKERRQ(ierr); 2231 if (!a->solve_work) { 2232 ierr = PetscMalloc1((inA->rmap->N+inA->rmap->bs),&a->solve_work);CHKERRQ(ierr); 2233 ierr = PetscLogObjectMemory((PetscObject)inA,(inA->rmap->N+inA->rmap->bs)*sizeof(PetscScalar));CHKERRQ(ierr); 2234 } 2235 ierr = MatLUFactorNumeric(outA,inA,info);CHKERRQ(ierr); 2236 PetscFunctionReturn(0); 2237 } 2238 2239 #undef __FUNCT__ 2240 #define __FUNCT__ "MatSeqBAIJSetColumnIndices_SeqBAIJ" 2241 PetscErrorCode MatSeqBAIJSetColumnIndices_SeqBAIJ(Mat mat,PetscInt *indices) 2242 { 2243 Mat_SeqBAIJ *baij = (Mat_SeqBAIJ*)mat->data; 2244 PetscInt i,nz,mbs; 2245 2246 PetscFunctionBegin; 2247 nz = baij->maxnz; 2248 mbs = baij->mbs; 2249 for (i=0; i<nz; i++) { 2250 baij->j[i] = indices[i]; 2251 } 2252 baij->nz = nz; 2253 for (i=0; i<mbs; i++) { 2254 baij->ilen[i] = baij->imax[i]; 2255 } 2256 PetscFunctionReturn(0); 2257 } 2258 2259 #undef __FUNCT__ 2260 #define __FUNCT__ "MatSeqBAIJSetColumnIndices" 2261 /*@ 2262 MatSeqBAIJSetColumnIndices - Set the column indices for all the rows 2263 in the matrix. 2264 2265 Input Parameters: 2266 + mat - the SeqBAIJ matrix 2267 - indices - the column indices 2268 2269 Level: advanced 2270 2271 Notes: 2272 This can be called if you have precomputed the nonzero structure of the 2273 matrix and want to provide it to the matrix object to improve the performance 2274 of the MatSetValues() operation. 2275 2276 You MUST have set the correct numbers of nonzeros per row in the call to 2277 MatCreateSeqBAIJ(), and the columns indices MUST be sorted. 2278 2279 MUST be called before any calls to MatSetValues(); 2280 2281 @*/ 2282 PetscErrorCode MatSeqBAIJSetColumnIndices(Mat mat,PetscInt *indices) 2283 { 2284 PetscErrorCode ierr; 2285 2286 PetscFunctionBegin; 2287 PetscValidHeaderSpecific(mat,MAT_CLASSID,1); 2288 PetscValidPointer(indices,2); 2289 ierr = PetscUseMethod(mat,"MatSeqBAIJSetColumnIndices_C",(Mat,PetscInt*),(mat,indices));CHKERRQ(ierr); 2290 PetscFunctionReturn(0); 2291 } 2292 2293 #undef __FUNCT__ 2294 #define __FUNCT__ "MatGetRowMaxAbs_SeqBAIJ" 2295 PetscErrorCode MatGetRowMaxAbs_SeqBAIJ(Mat A,Vec v,PetscInt idx[]) 2296 { 2297 Mat_SeqBAIJ *a = (Mat_SeqBAIJ*)A->data; 2298 PetscErrorCode ierr; 2299 PetscInt i,j,n,row,bs,*ai,*aj,mbs; 2300 PetscReal atmp; 2301 PetscScalar *x,zero = 0.0; 2302 MatScalar *aa; 2303 PetscInt ncols,brow,krow,kcol; 2304 2305 PetscFunctionBegin; 2306 if (A->factortype) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Not for factored matrix"); 2307 bs = A->rmap->bs; 2308 aa = a->a; 2309 ai = a->i; 2310 aj = a->j; 2311 mbs = a->mbs; 2312 2313 ierr = VecSet(v,zero);CHKERRQ(ierr); 2314 ierr = VecGetArray(v,&x);CHKERRQ(ierr); 2315 ierr = VecGetLocalSize(v,&n);CHKERRQ(ierr); 2316 if (n != A->rmap->N) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Nonconforming matrix and vector"); 2317 for (i=0; i<mbs; i++) { 2318 ncols = ai[1] - ai[0]; ai++; 2319 brow = bs*i; 2320 for (j=0; j<ncols; j++) { 2321 for (kcol=0; kcol<bs; kcol++) { 2322 for (krow=0; krow<bs; krow++) { 2323 atmp = PetscAbsScalar(*aa);aa++; 2324 row = brow + krow; /* row index */ 2325 if (PetscAbsScalar(x[row]) < atmp) {x[row] = atmp; if (idx) idx[row] = bs*(*aj) + kcol;} 2326 } 2327 } 2328 aj++; 2329 } 2330 } 2331 ierr = VecRestoreArray(v,&x);CHKERRQ(ierr); 2332 PetscFunctionReturn(0); 2333 } 2334 2335 #undef __FUNCT__ 2336 #define __FUNCT__ "MatCopy_SeqBAIJ" 2337 PetscErrorCode MatCopy_SeqBAIJ(Mat A,Mat B,MatStructure str) 2338 { 2339 PetscErrorCode ierr; 2340 2341 PetscFunctionBegin; 2342 /* If the two matrices have the same copy implementation, use fast copy. */ 2343 if (str == SAME_NONZERO_PATTERN && (A->ops->copy == B->ops->copy)) { 2344 Mat_SeqBAIJ *a = (Mat_SeqBAIJ*)A->data; 2345 Mat_SeqBAIJ *b = (Mat_SeqBAIJ*)B->data; 2346 PetscInt ambs=a->mbs,bmbs=b->mbs,abs=A->rmap->bs,bbs=B->rmap->bs,bs2=abs*abs; 2347 2348 if (a->i[ambs] != b->i[bmbs]) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_INCOMP,"Number of nonzero blocks in matrices A %D and B %D are different",a->i[ambs],b->i[bmbs]); 2349 if (abs != bbs) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_INCOMP,"Block size A %D and B %D are different",abs,bbs); 2350 ierr = PetscMemcpy(b->a,a->a,(bs2*a->i[ambs])*sizeof(PetscScalar));CHKERRQ(ierr); 2351 } else { 2352 ierr = MatCopy_Basic(A,B,str);CHKERRQ(ierr); 2353 } 2354 PetscFunctionReturn(0); 2355 } 2356 2357 #undef __FUNCT__ 2358 #define __FUNCT__ "MatSetUp_SeqBAIJ" 2359 PetscErrorCode MatSetUp_SeqBAIJ(Mat A) 2360 { 2361 PetscErrorCode ierr; 2362 2363 PetscFunctionBegin; 2364 ierr = MatSeqBAIJSetPreallocation_SeqBAIJ(A,A->rmap->bs,PETSC_DEFAULT,0);CHKERRQ(ierr); 2365 PetscFunctionReturn(0); 2366 } 2367 2368 #undef __FUNCT__ 2369 #define __FUNCT__ "MatSeqBAIJGetArray_SeqBAIJ" 2370 PetscErrorCode MatSeqBAIJGetArray_SeqBAIJ(Mat A,PetscScalar *array[]) 2371 { 2372 Mat_SeqBAIJ *a = (Mat_SeqBAIJ*)A->data; 2373 2374 PetscFunctionBegin; 2375 *array = a->a; 2376 PetscFunctionReturn(0); 2377 } 2378 2379 #undef __FUNCT__ 2380 #define __FUNCT__ "MatSeqBAIJRestoreArray_SeqBAIJ" 2381 PetscErrorCode MatSeqBAIJRestoreArray_SeqBAIJ(Mat A,PetscScalar *array[]) 2382 { 2383 PetscFunctionBegin; 2384 PetscFunctionReturn(0); 2385 } 2386 2387 #undef __FUNCT__ 2388 #define __FUNCT__ "MatAXPY_SeqBAIJ" 2389 PetscErrorCode MatAXPY_SeqBAIJ(Mat Y,PetscScalar a,Mat X,MatStructure str) 2390 { 2391 Mat_SeqBAIJ *x = (Mat_SeqBAIJ*)X->data,*y = (Mat_SeqBAIJ*)Y->data; 2392 PetscErrorCode ierr; 2393 PetscInt i,bs=Y->rmap->bs,j,bs2=bs*bs; 2394 PetscBLASInt one=1; 2395 2396 PetscFunctionBegin; 2397 if (str == SAME_NONZERO_PATTERN) { 2398 PetscScalar alpha = a; 2399 PetscBLASInt bnz; 2400 ierr = PetscBLASIntCast(x->nz*bs2,&bnz);CHKERRQ(ierr); 2401 PetscStackCallBLAS("BLASaxpy",BLASaxpy_(&bnz,&alpha,x->a,&one,y->a,&one)); 2402 ierr = PetscObjectStateIncrease((PetscObject)Y);CHKERRQ(ierr); 2403 } else if (str == SUBSET_NONZERO_PATTERN) { /* nonzeros of X is a subset of Y's */ 2404 if (y->xtoy && y->XtoY != X) { 2405 ierr = PetscFree(y->xtoy);CHKERRQ(ierr); 2406 ierr = MatDestroy(&y->XtoY);CHKERRQ(ierr); 2407 } 2408 if (!y->xtoy) { /* get xtoy */ 2409 ierr = MatAXPYGetxtoy_Private(x->mbs,x->i,x->j,NULL, y->i,y->j,NULL, &y->xtoy);CHKERRQ(ierr); 2410 y->XtoY = X; 2411 ierr = PetscObjectReference((PetscObject)X);CHKERRQ(ierr); 2412 } 2413 for (i=0; i<x->nz; i++) { 2414 j = 0; 2415 while (j < bs2) { 2416 y->a[bs2*y->xtoy[i]+j] += a*(x->a[bs2*i+j]); 2417 j++; 2418 } 2419 } 2420 ierr = PetscObjectStateIncrease((PetscObject)Y);CHKERRQ(ierr); 2421 ierr = PetscInfo3(Y,"ratio of nnz(X)/nnz(Y): %D/%D = %g\n",bs2*x->nz,bs2*y->nz,(double)((PetscReal)(bs2*x->nz)/(bs2*y->nz)));CHKERRQ(ierr); 2422 } else { 2423 ierr = MatAXPY_Basic(Y,a,X,str);CHKERRQ(ierr); 2424 } 2425 PetscFunctionReturn(0); 2426 } 2427 2428 #undef __FUNCT__ 2429 #define __FUNCT__ "MatRealPart_SeqBAIJ" 2430 PetscErrorCode MatRealPart_SeqBAIJ(Mat A) 2431 { 2432 Mat_SeqBAIJ *a = (Mat_SeqBAIJ*)A->data; 2433 PetscInt i,nz = a->bs2*a->i[a->mbs]; 2434 MatScalar *aa = a->a; 2435 2436 PetscFunctionBegin; 2437 for (i=0; i<nz; i++) aa[i] = PetscRealPart(aa[i]); 2438 PetscFunctionReturn(0); 2439 } 2440 2441 #undef __FUNCT__ 2442 #define __FUNCT__ "MatImaginaryPart_SeqBAIJ" 2443 PetscErrorCode MatImaginaryPart_SeqBAIJ(Mat A) 2444 { 2445 Mat_SeqBAIJ *a = (Mat_SeqBAIJ*)A->data; 2446 PetscInt i,nz = a->bs2*a->i[a->mbs]; 2447 MatScalar *aa = a->a; 2448 2449 PetscFunctionBegin; 2450 for (i=0; i<nz; i++) aa[i] = PetscImaginaryPart(aa[i]); 2451 PetscFunctionReturn(0); 2452 } 2453 2454 #undef __FUNCT__ 2455 #define __FUNCT__ "MatGetColumnIJ_SeqBAIJ" 2456 /* 2457 Code almost idential to MatGetColumnIJ_SeqAIJ() should share common code 2458 */ 2459 PetscErrorCode MatGetColumnIJ_SeqBAIJ(Mat A,PetscInt oshift,PetscBool symmetric,PetscBool inodecompressed,PetscInt *nn,const PetscInt *ia[],const PetscInt *ja[],PetscBool *done) 2460 { 2461 Mat_SeqBAIJ *a = (Mat_SeqBAIJ*)A->data; 2462 PetscErrorCode ierr; 2463 PetscInt bs = A->rmap->bs,i,*collengths,*cia,*cja,n = A->cmap->n/bs,m = A->rmap->n/bs; 2464 PetscInt nz = a->i[m],row,*jj,mr,col; 2465 2466 PetscFunctionBegin; 2467 *nn = n; 2468 if (!ia) PetscFunctionReturn(0); 2469 if (symmetric) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"Not for BAIJ matrices"); 2470 else { 2471 ierr = PetscCalloc1((n+1),&collengths);CHKERRQ(ierr); 2472 ierr = PetscMalloc1((n+1),&cia);CHKERRQ(ierr); 2473 ierr = PetscMalloc1((nz+1),&cja);CHKERRQ(ierr); 2474 jj = a->j; 2475 for (i=0; i<nz; i++) { 2476 collengths[jj[i]]++; 2477 } 2478 cia[0] = oshift; 2479 for (i=0; i<n; i++) { 2480 cia[i+1] = cia[i] + collengths[i]; 2481 } 2482 ierr = PetscMemzero(collengths,n*sizeof(PetscInt));CHKERRQ(ierr); 2483 jj = a->j; 2484 for (row=0; row<m; row++) { 2485 mr = a->i[row+1] - a->i[row]; 2486 for (i=0; i<mr; i++) { 2487 col = *jj++; 2488 2489 cja[cia[col] + collengths[col]++ - oshift] = row + oshift; 2490 } 2491 } 2492 ierr = PetscFree(collengths);CHKERRQ(ierr); 2493 *ia = cia; *ja = cja; 2494 } 2495 PetscFunctionReturn(0); 2496 } 2497 2498 #undef __FUNCT__ 2499 #define __FUNCT__ "MatRestoreColumnIJ_SeqBAIJ" 2500 PetscErrorCode MatRestoreColumnIJ_SeqBAIJ(Mat A,PetscInt oshift,PetscBool symmetric,PetscBool inodecompressed,PetscInt *n,const PetscInt *ia[],const PetscInt *ja[],PetscBool *done) 2501 { 2502 PetscErrorCode ierr; 2503 2504 PetscFunctionBegin; 2505 if (!ia) PetscFunctionReturn(0); 2506 ierr = PetscFree(*ia);CHKERRQ(ierr); 2507 ierr = PetscFree(*ja);CHKERRQ(ierr); 2508 PetscFunctionReturn(0); 2509 } 2510 2511 /* 2512 MatGetColumnIJ_SeqBAIJ_Color() and MatRestoreColumnIJ_SeqBAIJ_Color() are customized from 2513 MatGetColumnIJ_SeqBAIJ() and MatRestoreColumnIJ_SeqBAIJ() by adding an output 2514 spidx[], index of a->a, to be used in MatTransposeColoringCreate() and MatFDColoringCreate() 2515 */ 2516 #undef __FUNCT__ 2517 #define __FUNCT__ "MatGetColumnIJ_SeqBAIJ_Color" 2518 PetscErrorCode MatGetColumnIJ_SeqBAIJ_Color(Mat A,PetscInt oshift,PetscBool symmetric,PetscBool inodecompressed,PetscInt *nn,const PetscInt *ia[],const PetscInt *ja[],PetscInt *spidx[],PetscBool *done) 2519 { 2520 Mat_SeqBAIJ *a = (Mat_SeqBAIJ*)A->data; 2521 PetscErrorCode ierr; 2522 PetscInt i,*collengths,*cia,*cja,n=a->nbs,m=a->mbs; 2523 PetscInt nz = a->i[m],row,*jj,mr,col; 2524 PetscInt *cspidx; 2525 2526 PetscFunctionBegin; 2527 *nn = n; 2528 if (!ia) PetscFunctionReturn(0); 2529 2530 ierr = PetscCalloc1((n+1),&collengths);CHKERRQ(ierr); 2531 ierr = PetscMalloc1((n+1),&cia);CHKERRQ(ierr); 2532 ierr = PetscMalloc1((nz+1),&cja);CHKERRQ(ierr); 2533 ierr = PetscMalloc1((nz+1),&cspidx);CHKERRQ(ierr); 2534 jj = a->j; 2535 for (i=0; i<nz; i++) { 2536 collengths[jj[i]]++; 2537 } 2538 cia[0] = oshift; 2539 for (i=0; i<n; i++) { 2540 cia[i+1] = cia[i] + collengths[i]; 2541 } 2542 ierr = PetscMemzero(collengths,n*sizeof(PetscInt));CHKERRQ(ierr); 2543 jj = a->j; 2544 for (row=0; row<m; row++) { 2545 mr = a->i[row+1] - a->i[row]; 2546 for (i=0; i<mr; i++) { 2547 col = *jj++; 2548 cspidx[cia[col] + collengths[col] - oshift] = a->i[row] + i; /* index of a->j */ 2549 cja[cia[col] + collengths[col]++ - oshift] = row + oshift; 2550 } 2551 } 2552 ierr = PetscFree(collengths);CHKERRQ(ierr); 2553 *ia = cia; *ja = cja; 2554 *spidx = cspidx; 2555 PetscFunctionReturn(0); 2556 } 2557 2558 #undef __FUNCT__ 2559 #define __FUNCT__ "MatRestoreColumnIJ_SeqBAIJ_Color" 2560 PetscErrorCode MatRestoreColumnIJ_SeqBAIJ_Color(Mat A,PetscInt oshift,PetscBool symmetric,PetscBool inodecompressed,PetscInt *n,const PetscInt *ia[],const PetscInt *ja[],PetscInt *spidx[],PetscBool *done) 2561 { 2562 PetscErrorCode ierr; 2563 2564 PetscFunctionBegin; 2565 ierr = MatRestoreColumnIJ_SeqBAIJ(A,oshift,symmetric,inodecompressed,n,ia,ja,done);CHKERRQ(ierr); 2566 ierr = PetscFree(*spidx);CHKERRQ(ierr); 2567 PetscFunctionReturn(0); 2568 } 2569 2570 /* -------------------------------------------------------------------*/ 2571 static struct _MatOps MatOps_Values = {MatSetValues_SeqBAIJ, 2572 MatGetRow_SeqBAIJ, 2573 MatRestoreRow_SeqBAIJ, 2574 MatMult_SeqBAIJ_N, 2575 /* 4*/ MatMultAdd_SeqBAIJ_N, 2576 MatMultTranspose_SeqBAIJ, 2577 MatMultTransposeAdd_SeqBAIJ, 2578 0, 2579 0, 2580 0, 2581 /* 10*/ 0, 2582 MatLUFactor_SeqBAIJ, 2583 0, 2584 0, 2585 MatTranspose_SeqBAIJ, 2586 /* 15*/ MatGetInfo_SeqBAIJ, 2587 MatEqual_SeqBAIJ, 2588 MatGetDiagonal_SeqBAIJ, 2589 MatDiagonalScale_SeqBAIJ, 2590 MatNorm_SeqBAIJ, 2591 /* 20*/ 0, 2592 MatAssemblyEnd_SeqBAIJ, 2593 MatSetOption_SeqBAIJ, 2594 MatZeroEntries_SeqBAIJ, 2595 /* 24*/ MatZeroRows_SeqBAIJ, 2596 0, 2597 0, 2598 0, 2599 0, 2600 /* 29*/ MatSetUp_SeqBAIJ, 2601 0, 2602 0, 2603 0, 2604 0, 2605 /* 34*/ MatDuplicate_SeqBAIJ, 2606 0, 2607 0, 2608 MatILUFactor_SeqBAIJ, 2609 0, 2610 /* 39*/ MatAXPY_SeqBAIJ, 2611 MatGetSubMatrices_SeqBAIJ, 2612 MatIncreaseOverlap_SeqBAIJ, 2613 MatGetValues_SeqBAIJ, 2614 MatCopy_SeqBAIJ, 2615 /* 44*/ 0, 2616 MatScale_SeqBAIJ, 2617 0, 2618 0, 2619 MatZeroRowsColumns_SeqBAIJ, 2620 /* 49*/ 0, 2621 MatGetRowIJ_SeqBAIJ, 2622 MatRestoreRowIJ_SeqBAIJ, 2623 MatGetColumnIJ_SeqBAIJ, 2624 MatRestoreColumnIJ_SeqBAIJ, 2625 /* 54*/ MatFDColoringCreate_SeqXAIJ, 2626 0, 2627 0, 2628 0, 2629 MatSetValuesBlocked_SeqBAIJ, 2630 /* 59*/ MatGetSubMatrix_SeqBAIJ, 2631 MatDestroy_SeqBAIJ, 2632 MatView_SeqBAIJ, 2633 0, 2634 0, 2635 /* 64*/ 0, 2636 0, 2637 0, 2638 0, 2639 0, 2640 /* 69*/ MatGetRowMaxAbs_SeqBAIJ, 2641 0, 2642 MatConvert_Basic, 2643 0, 2644 0, 2645 /* 74*/ 0, 2646 MatFDColoringApply_BAIJ, 2647 0, 2648 0, 2649 0, 2650 /* 79*/ 0, 2651 0, 2652 0, 2653 0, 2654 MatLoad_SeqBAIJ, 2655 /* 84*/ 0, 2656 0, 2657 0, 2658 0, 2659 0, 2660 /* 89*/ 0, 2661 0, 2662 0, 2663 0, 2664 0, 2665 /* 94*/ 0, 2666 0, 2667 0, 2668 0, 2669 0, 2670 /* 99*/ 0, 2671 0, 2672 0, 2673 0, 2674 0, 2675 /*104*/ 0, 2676 MatRealPart_SeqBAIJ, 2677 MatImaginaryPart_SeqBAIJ, 2678 0, 2679 0, 2680 /*109*/ 0, 2681 0, 2682 0, 2683 0, 2684 MatMissingDiagonal_SeqBAIJ, 2685 /*114*/ 0, 2686 0, 2687 0, 2688 0, 2689 0, 2690 /*119*/ 0, 2691 0, 2692 MatMultHermitianTranspose_SeqBAIJ, 2693 MatMultHermitianTransposeAdd_SeqBAIJ, 2694 0, 2695 /*124*/ 0, 2696 0, 2697 MatInvertBlockDiagonal_SeqBAIJ, 2698 0, 2699 0, 2700 /*129*/ 0, 2701 0, 2702 0, 2703 0, 2704 0, 2705 /*134*/ 0, 2706 0, 2707 0, 2708 0, 2709 0, 2710 /*139*/ 0, 2711 0, 2712 0, 2713 MatFDColoringSetUp_SeqXAIJ 2714 }; 2715 2716 #undef __FUNCT__ 2717 #define __FUNCT__ "MatStoreValues_SeqBAIJ" 2718 PetscErrorCode MatStoreValues_SeqBAIJ(Mat mat) 2719 { 2720 Mat_SeqBAIJ *aij = (Mat_SeqBAIJ*)mat->data; 2721 PetscInt nz = aij->i[aij->mbs]*aij->bs2; 2722 PetscErrorCode ierr; 2723 2724 PetscFunctionBegin; 2725 if (aij->nonew != 1) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ORDER,"Must call MatSetOption(A,MAT_NEW_NONZERO_LOCATIONS,PETSC_FALSE);first"); 2726 2727 /* allocate space for values if not already there */ 2728 if (!aij->saved_values) { 2729 ierr = PetscMalloc1((nz+1),&aij->saved_values);CHKERRQ(ierr); 2730 ierr = PetscLogObjectMemory((PetscObject)mat,(nz+1)*sizeof(PetscScalar));CHKERRQ(ierr); 2731 } 2732 2733 /* copy values over */ 2734 ierr = PetscMemcpy(aij->saved_values,aij->a,nz*sizeof(PetscScalar));CHKERRQ(ierr); 2735 PetscFunctionReturn(0); 2736 } 2737 2738 #undef __FUNCT__ 2739 #define __FUNCT__ "MatRetrieveValues_SeqBAIJ" 2740 PetscErrorCode MatRetrieveValues_SeqBAIJ(Mat mat) 2741 { 2742 Mat_SeqBAIJ *aij = (Mat_SeqBAIJ*)mat->data; 2743 PetscErrorCode ierr; 2744 PetscInt nz = aij->i[aij->mbs]*aij->bs2; 2745 2746 PetscFunctionBegin; 2747 if (aij->nonew != 1) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ORDER,"Must call MatSetOption(A,MAT_NEW_NONZERO_LOCATIONS,PETSC_FALSE);first"); 2748 if (!aij->saved_values) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ORDER,"Must call MatStoreValues(A);first"); 2749 2750 /* copy values over */ 2751 ierr = PetscMemcpy(aij->a,aij->saved_values,nz*sizeof(PetscScalar));CHKERRQ(ierr); 2752 PetscFunctionReturn(0); 2753 } 2754 2755 PETSC_EXTERN PetscErrorCode MatConvert_SeqBAIJ_SeqAIJ(Mat, MatType,MatReuse,Mat*); 2756 PETSC_EXTERN PetscErrorCode MatConvert_SeqBAIJ_SeqSBAIJ(Mat, MatType,MatReuse,Mat*); 2757 2758 #undef __FUNCT__ 2759 #define __FUNCT__ "MatSeqBAIJSetPreallocation_SeqBAIJ" 2760 PetscErrorCode MatSeqBAIJSetPreallocation_SeqBAIJ(Mat B,PetscInt bs,PetscInt nz,PetscInt *nnz) 2761 { 2762 Mat_SeqBAIJ *b; 2763 PetscErrorCode ierr; 2764 PetscInt i,mbs,nbs,bs2; 2765 PetscBool flg,skipallocation = PETSC_FALSE,realalloc = PETSC_FALSE; 2766 2767 PetscFunctionBegin; 2768 if (nz >= 0 || nnz) realalloc = PETSC_TRUE; 2769 if (nz == MAT_SKIP_ALLOCATION) { 2770 skipallocation = PETSC_TRUE; 2771 nz = 0; 2772 } 2773 2774 ierr = MatSetBlockSize(B,PetscAbs(bs));CHKERRQ(ierr); 2775 ierr = PetscLayoutSetUp(B->rmap);CHKERRQ(ierr); 2776 ierr = PetscLayoutSetUp(B->cmap);CHKERRQ(ierr); 2777 ierr = PetscLayoutGetBlockSize(B->rmap,&bs);CHKERRQ(ierr); 2778 2779 B->preallocated = PETSC_TRUE; 2780 2781 mbs = B->rmap->n/bs; 2782 nbs = B->cmap->n/bs; 2783 bs2 = bs*bs; 2784 2785 if (mbs*bs!=B->rmap->n || nbs*bs!=B->cmap->n) SETERRQ3(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Number rows %D, cols %D must be divisible by blocksize %D",B->rmap->N,B->cmap->n,bs); 2786 2787 if (nz == PETSC_DEFAULT || nz == PETSC_DECIDE) nz = 5; 2788 if (nz < 0) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"nz cannot be less than 0: value %D",nz); 2789 if (nnz) { 2790 for (i=0; i<mbs; i++) { 2791 if (nnz[i] < 0) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"nnz cannot be less than 0: local row %D value %D",i,nnz[i]); 2792 if (nnz[i] > nbs) SETERRQ3(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"nnz cannot be greater than block row length: local row %D value %D rowlength %D",i,nnz[i],nbs); 2793 } 2794 } 2795 2796 b = (Mat_SeqBAIJ*)B->data; 2797 ierr = PetscOptionsBegin(PetscObjectComm((PetscObject)B),NULL,"Optimize options for SEQBAIJ matrix 2 ","Mat");CHKERRQ(ierr); 2798 ierr = PetscOptionsBool("-mat_no_unroll","Do not optimize for block size (slow)",NULL,PETSC_FALSE,&flg,NULL);CHKERRQ(ierr); 2799 ierr = PetscOptionsEnd();CHKERRQ(ierr); 2800 2801 if (!flg) { 2802 switch (bs) { 2803 case 1: 2804 B->ops->mult = MatMult_SeqBAIJ_1; 2805 B->ops->multadd = MatMultAdd_SeqBAIJ_1; 2806 break; 2807 case 2: 2808 B->ops->mult = MatMult_SeqBAIJ_2; 2809 B->ops->multadd = MatMultAdd_SeqBAIJ_2; 2810 break; 2811 case 3: 2812 B->ops->mult = MatMult_SeqBAIJ_3; 2813 B->ops->multadd = MatMultAdd_SeqBAIJ_3; 2814 break; 2815 case 4: 2816 B->ops->mult = MatMult_SeqBAIJ_4; 2817 B->ops->multadd = MatMultAdd_SeqBAIJ_4; 2818 break; 2819 case 5: 2820 B->ops->mult = MatMult_SeqBAIJ_5; 2821 B->ops->multadd = MatMultAdd_SeqBAIJ_5; 2822 break; 2823 case 6: 2824 B->ops->mult = MatMult_SeqBAIJ_6; 2825 B->ops->multadd = MatMultAdd_SeqBAIJ_6; 2826 break; 2827 case 7: 2828 B->ops->mult = MatMult_SeqBAIJ_7; 2829 B->ops->multadd = MatMultAdd_SeqBAIJ_7; 2830 break; 2831 case 15: 2832 B->ops->mult = MatMult_SeqBAIJ_15_ver1; 2833 B->ops->multadd = MatMultAdd_SeqBAIJ_N; 2834 break; 2835 default: 2836 B->ops->mult = MatMult_SeqBAIJ_N; 2837 B->ops->multadd = MatMultAdd_SeqBAIJ_N; 2838 break; 2839 } 2840 } 2841 B->ops->sor = MatSOR_SeqBAIJ; 2842 b->mbs = mbs; 2843 b->nbs = nbs; 2844 if (!skipallocation) { 2845 if (!b->imax) { 2846 ierr = PetscMalloc2(mbs,&b->imax,mbs,&b->ilen);CHKERRQ(ierr); 2847 ierr = PetscLogObjectMemory((PetscObject)B,2*mbs*sizeof(PetscInt));CHKERRQ(ierr); 2848 2849 b->free_imax_ilen = PETSC_TRUE; 2850 } 2851 /* b->ilen will count nonzeros in each block row so far. */ 2852 for (i=0; i<mbs; i++) b->ilen[i] = 0; 2853 if (!nnz) { 2854 if (nz == PETSC_DEFAULT || nz == PETSC_DECIDE) nz = 5; 2855 else if (nz < 0) nz = 1; 2856 for (i=0; i<mbs; i++) b->imax[i] = nz; 2857 nz = nz*mbs; 2858 } else { 2859 nz = 0; 2860 for (i=0; i<mbs; i++) {b->imax[i] = nnz[i]; nz += nnz[i];} 2861 } 2862 2863 /* allocate the matrix space */ 2864 ierr = MatSeqXAIJFreeAIJ(B,&b->a,&b->j,&b->i);CHKERRQ(ierr); 2865 ierr = PetscMalloc3(bs2*nz,&b->a,nz,&b->j,B->rmap->N+1,&b->i);CHKERRQ(ierr); 2866 ierr = PetscLogObjectMemory((PetscObject)B,(B->rmap->N+1)*sizeof(PetscInt)+nz*(bs2*sizeof(PetscScalar)+sizeof(PetscInt)));CHKERRQ(ierr); 2867 ierr = PetscMemzero(b->a,nz*bs2*sizeof(MatScalar));CHKERRQ(ierr); 2868 ierr = PetscMemzero(b->j,nz*sizeof(PetscInt));CHKERRQ(ierr); 2869 2870 b->singlemalloc = PETSC_TRUE; 2871 b->i[0] = 0; 2872 for (i=1; i<mbs+1; i++) { 2873 b->i[i] = b->i[i-1] + b->imax[i-1]; 2874 } 2875 b->free_a = PETSC_TRUE; 2876 b->free_ij = PETSC_TRUE; 2877 #if defined(PETSC_THREADCOMM_ACTIVE) 2878 ierr = MatZeroEntries_SeqBAIJ(B);CHKERRQ(ierr); 2879 #endif 2880 } else { 2881 b->free_a = PETSC_FALSE; 2882 b->free_ij = PETSC_FALSE; 2883 } 2884 2885 b->bs2 = bs2; 2886 b->mbs = mbs; 2887 b->nz = 0; 2888 b->maxnz = nz; 2889 B->info.nz_unneeded = (PetscReal)b->maxnz*bs2; 2890 if (realalloc) {ierr = MatSetOption(B,MAT_NEW_NONZERO_ALLOCATION_ERR,PETSC_TRUE);CHKERRQ(ierr);} 2891 PetscFunctionReturn(0); 2892 } 2893 2894 #undef __FUNCT__ 2895 #define __FUNCT__ "MatSeqBAIJSetPreallocationCSR_SeqBAIJ" 2896 PetscErrorCode MatSeqBAIJSetPreallocationCSR_SeqBAIJ(Mat B,PetscInt bs,const PetscInt ii[],const PetscInt jj[],const PetscScalar V[]) 2897 { 2898 PetscInt i,m,nz,nz_max=0,*nnz; 2899 PetscScalar *values=0; 2900 PetscBool roworiented = ((Mat_SeqBAIJ*)B->data)->roworiented; 2901 PetscErrorCode ierr; 2902 2903 PetscFunctionBegin; 2904 if (bs < 1) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Invalid block size specified, must be positive but it is %D",bs); 2905 ierr = PetscLayoutSetBlockSize(B->rmap,bs);CHKERRQ(ierr); 2906 ierr = PetscLayoutSetBlockSize(B->cmap,bs);CHKERRQ(ierr); 2907 ierr = PetscLayoutSetUp(B->rmap);CHKERRQ(ierr); 2908 ierr = PetscLayoutSetUp(B->cmap);CHKERRQ(ierr); 2909 ierr = PetscLayoutGetBlockSize(B->rmap,&bs);CHKERRQ(ierr); 2910 m = B->rmap->n/bs; 2911 2912 if (ii[0] != 0) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE, "ii[0] must be 0 but it is %D",ii[0]); 2913 ierr = PetscMalloc1((m+1), &nnz);CHKERRQ(ierr); 2914 for (i=0; i<m; i++) { 2915 nz = ii[i+1]- ii[i]; 2916 if (nz < 0) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE, "Local row %D has a negative number of columns %D",i,nz); 2917 nz_max = PetscMax(nz_max, nz); 2918 nnz[i] = nz; 2919 } 2920 ierr = MatSeqBAIJSetPreallocation(B,bs,0,nnz);CHKERRQ(ierr); 2921 ierr = PetscFree(nnz);CHKERRQ(ierr); 2922 2923 values = (PetscScalar*)V; 2924 if (!values) { 2925 ierr = PetscCalloc1(bs*bs*(nz_max+1),&values);CHKERRQ(ierr); 2926 } 2927 for (i=0; i<m; i++) { 2928 PetscInt ncols = ii[i+1] - ii[i]; 2929 const PetscInt *icols = jj + ii[i]; 2930 const PetscScalar *svals = values + (V ? (bs*bs*ii[i]) : 0); 2931 if (!roworiented) { 2932 ierr = MatSetValuesBlocked_SeqBAIJ(B,1,&i,ncols,icols,svals,INSERT_VALUES);CHKERRQ(ierr); 2933 } else { 2934 PetscInt j; 2935 for (j=0; j<ncols; j++) { 2936 const PetscScalar *svals = values + (V ? (bs*bs*(ii[i]+j)) : 0); 2937 ierr = MatSetValuesBlocked_SeqBAIJ(B,1,&i,1,&icols[j],svals,INSERT_VALUES);CHKERRQ(ierr); 2938 } 2939 } 2940 } 2941 if (!V) { ierr = PetscFree(values);CHKERRQ(ierr); } 2942 ierr = MatAssemblyBegin(B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 2943 ierr = MatAssemblyEnd(B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 2944 ierr = MatSetOption(B,MAT_NEW_NONZERO_LOCATION_ERR,PETSC_TRUE);CHKERRQ(ierr); 2945 PetscFunctionReturn(0); 2946 } 2947 2948 PETSC_EXTERN PetscErrorCode MatGetFactor_seqbaij_petsc(Mat,MatFactorType,Mat*); 2949 PETSC_EXTERN PetscErrorCode MatGetFactor_seqbaij_bstrm(Mat,MatFactorType,Mat*); 2950 #if defined(PETSC_HAVE_MUMPS) 2951 PETSC_EXTERN PetscErrorCode MatGetFactor_baij_mumps(Mat,MatFactorType,Mat*); 2952 #endif 2953 extern PetscErrorCode MatGetFactorAvailable_seqbaij_petsc(Mat,MatFactorType,PetscBool*); 2954 2955 /*MC 2956 MATSEQBAIJ - MATSEQBAIJ = "seqbaij" - A matrix type to be used for sequential block sparse matrices, based on 2957 block sparse compressed row format. 2958 2959 Options Database Keys: 2960 . -mat_type seqbaij - sets the matrix type to "seqbaij" during a call to MatSetFromOptions() 2961 2962 Level: beginner 2963 2964 .seealso: MatCreateSeqBAIJ() 2965 M*/ 2966 2967 PETSC_EXTERN PetscErrorCode MatConvert_SeqBAIJ_SeqBSTRM(Mat, MatType,MatReuse,Mat*); 2968 2969 #undef __FUNCT__ 2970 #define __FUNCT__ "MatCreate_SeqBAIJ" 2971 PETSC_EXTERN PetscErrorCode MatCreate_SeqBAIJ(Mat B) 2972 { 2973 PetscErrorCode ierr; 2974 PetscMPIInt size; 2975 Mat_SeqBAIJ *b; 2976 2977 PetscFunctionBegin; 2978 ierr = MPI_Comm_size(PetscObjectComm((PetscObject)B),&size);CHKERRQ(ierr); 2979 if (size > 1) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONG,"Comm must be of size 1"); 2980 2981 ierr = PetscNewLog(B,&b);CHKERRQ(ierr); 2982 B->data = (void*)b; 2983 ierr = PetscMemcpy(B->ops,&MatOps_Values,sizeof(struct _MatOps));CHKERRQ(ierr); 2984 2985 b->row = 0; 2986 b->col = 0; 2987 b->icol = 0; 2988 b->reallocs = 0; 2989 b->saved_values = 0; 2990 2991 b->roworiented = PETSC_TRUE; 2992 b->nonew = 0; 2993 b->diag = 0; 2994 b->solve_work = 0; 2995 b->mult_work = 0; 2996 B->spptr = 0; 2997 B->info.nz_unneeded = (PetscReal)b->maxnz*b->bs2; 2998 b->keepnonzeropattern = PETSC_FALSE; 2999 b->xtoy = 0; 3000 b->XtoY = 0; 3001 3002 ierr = PetscObjectComposeFunction((PetscObject)B,"MatGetFactorAvailable_petsc_C",MatGetFactorAvailable_seqbaij_petsc);CHKERRQ(ierr); 3003 ierr = PetscObjectComposeFunction((PetscObject)B,"MatGetFactor_petsc_C",MatGetFactor_seqbaij_petsc);CHKERRQ(ierr); 3004 ierr = PetscObjectComposeFunction((PetscObject)B,"MatGetFactor_bstrm_C",MatGetFactor_seqbaij_bstrm);CHKERRQ(ierr); 3005 #if defined(PETSC_HAVE_MUMPS) 3006 ierr = PetscObjectComposeFunction((PetscObject)B,"MatGetFactor_mumps_C", MatGetFactor_baij_mumps);CHKERRQ(ierr); 3007 #endif 3008 ierr = PetscObjectComposeFunction((PetscObject)B,"MatInvertBlockDiagonal_C",MatInvertBlockDiagonal_SeqBAIJ);CHKERRQ(ierr); 3009 ierr = PetscObjectComposeFunction((PetscObject)B,"MatStoreValues_C",MatStoreValues_SeqBAIJ);CHKERRQ(ierr); 3010 ierr = PetscObjectComposeFunction((PetscObject)B,"MatRetrieveValues_C",MatRetrieveValues_SeqBAIJ);CHKERRQ(ierr); 3011 ierr = PetscObjectComposeFunction((PetscObject)B,"MatSeqBAIJSetColumnIndices_C",MatSeqBAIJSetColumnIndices_SeqBAIJ);CHKERRQ(ierr); 3012 ierr = PetscObjectComposeFunction((PetscObject)B,"MatConvert_seqbaij_seqaij_C",MatConvert_SeqBAIJ_SeqAIJ);CHKERRQ(ierr); 3013 ierr = PetscObjectComposeFunction((PetscObject)B,"MatConvert_seqbaij_seqsbaij_C",MatConvert_SeqBAIJ_SeqSBAIJ);CHKERRQ(ierr); 3014 ierr = PetscObjectComposeFunction((PetscObject)B,"MatSeqBAIJSetPreallocation_C",MatSeqBAIJSetPreallocation_SeqBAIJ);CHKERRQ(ierr); 3015 ierr = PetscObjectComposeFunction((PetscObject)B,"MatSeqBAIJSetPreallocationCSR_C",MatSeqBAIJSetPreallocationCSR_SeqBAIJ);CHKERRQ(ierr); 3016 ierr = PetscObjectComposeFunction((PetscObject)B,"MatConvert_seqbaij_seqbstrm_C",MatConvert_SeqBAIJ_SeqBSTRM);CHKERRQ(ierr); 3017 ierr = PetscObjectComposeFunction((PetscObject)B,"MatIsTranspose_C",MatIsTranspose_SeqBAIJ);CHKERRQ(ierr); 3018 ierr = PetscObjectChangeTypeName((PetscObject)B,MATSEQBAIJ);CHKERRQ(ierr); 3019 PetscFunctionReturn(0); 3020 } 3021 3022 #undef __FUNCT__ 3023 #define __FUNCT__ "MatDuplicateNoCreate_SeqBAIJ" 3024 PetscErrorCode MatDuplicateNoCreate_SeqBAIJ(Mat C,Mat A,MatDuplicateOption cpvalues,PetscBool mallocmatspace) 3025 { 3026 Mat_SeqBAIJ *c = (Mat_SeqBAIJ*)C->data,*a = (Mat_SeqBAIJ*)A->data; 3027 PetscErrorCode ierr; 3028 PetscInt i,mbs = a->mbs,nz = a->nz,bs2 = a->bs2; 3029 3030 PetscFunctionBegin; 3031 if (a->i[mbs] != nz) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_PLIB,"Corrupt matrix"); 3032 3033 if (cpvalues == MAT_SHARE_NONZERO_PATTERN) { 3034 c->imax = a->imax; 3035 c->ilen = a->ilen; 3036 c->free_imax_ilen = PETSC_FALSE; 3037 } else { 3038 ierr = PetscMalloc2(mbs,&c->imax,mbs,&c->ilen);CHKERRQ(ierr); 3039 ierr = PetscLogObjectMemory((PetscObject)C,2*mbs*sizeof(PetscInt));CHKERRQ(ierr); 3040 for (i=0; i<mbs; i++) { 3041 c->imax[i] = a->imax[i]; 3042 c->ilen[i] = a->ilen[i]; 3043 } 3044 c->free_imax_ilen = PETSC_TRUE; 3045 } 3046 3047 /* allocate the matrix space */ 3048 if (mallocmatspace) { 3049 if (cpvalues == MAT_SHARE_NONZERO_PATTERN) { 3050 ierr = PetscCalloc1(bs2*nz,&c->a);CHKERRQ(ierr); 3051 ierr = PetscLogObjectMemory((PetscObject)C,a->i[mbs]*bs2*sizeof(PetscScalar));CHKERRQ(ierr); 3052 3053 c->i = a->i; 3054 c->j = a->j; 3055 c->singlemalloc = PETSC_FALSE; 3056 c->free_a = PETSC_TRUE; 3057 c->free_ij = PETSC_FALSE; 3058 c->parent = A; 3059 C->preallocated = PETSC_TRUE; 3060 C->assembled = PETSC_TRUE; 3061 3062 ierr = PetscObjectReference((PetscObject)A);CHKERRQ(ierr); 3063 ierr = MatSetOption(A,MAT_NEW_NONZERO_LOCATION_ERR,PETSC_TRUE);CHKERRQ(ierr); 3064 ierr = MatSetOption(C,MAT_NEW_NONZERO_LOCATION_ERR,PETSC_TRUE);CHKERRQ(ierr); 3065 } else { 3066 ierr = PetscMalloc3(bs2*nz,&c->a,nz,&c->j,mbs+1,&c->i);CHKERRQ(ierr); 3067 ierr = PetscLogObjectMemory((PetscObject)C,a->i[mbs]*(bs2*sizeof(PetscScalar)+sizeof(PetscInt))+(mbs+1)*sizeof(PetscInt));CHKERRQ(ierr); 3068 3069 c->singlemalloc = PETSC_TRUE; 3070 c->free_a = PETSC_TRUE; 3071 c->free_ij = PETSC_TRUE; 3072 3073 ierr = PetscMemcpy(c->i,a->i,(mbs+1)*sizeof(PetscInt));CHKERRQ(ierr); 3074 if (mbs > 0) { 3075 ierr = PetscMemcpy(c->j,a->j,nz*sizeof(PetscInt));CHKERRQ(ierr); 3076 if (cpvalues == MAT_COPY_VALUES) { 3077 ierr = PetscMemcpy(c->a,a->a,bs2*nz*sizeof(MatScalar));CHKERRQ(ierr); 3078 } else { 3079 ierr = PetscMemzero(c->a,bs2*nz*sizeof(MatScalar));CHKERRQ(ierr); 3080 } 3081 } 3082 C->preallocated = PETSC_TRUE; 3083 C->assembled = PETSC_TRUE; 3084 } 3085 } 3086 3087 c->roworiented = a->roworiented; 3088 c->nonew = a->nonew; 3089 3090 ierr = PetscLayoutReference(A->rmap,&C->rmap);CHKERRQ(ierr); 3091 ierr = PetscLayoutReference(A->cmap,&C->cmap);CHKERRQ(ierr); 3092 3093 c->bs2 = a->bs2; 3094 c->mbs = a->mbs; 3095 c->nbs = a->nbs; 3096 3097 if (a->diag) { 3098 if (cpvalues == MAT_SHARE_NONZERO_PATTERN) { 3099 c->diag = a->diag; 3100 c->free_diag = PETSC_FALSE; 3101 } else { 3102 ierr = PetscMalloc1((mbs+1),&c->diag);CHKERRQ(ierr); 3103 ierr = PetscLogObjectMemory((PetscObject)C,(mbs+1)*sizeof(PetscInt));CHKERRQ(ierr); 3104 for (i=0; i<mbs; i++) c->diag[i] = a->diag[i]; 3105 c->free_diag = PETSC_TRUE; 3106 } 3107 } else c->diag = 0; 3108 3109 c->nz = a->nz; 3110 c->maxnz = a->nz; /* Since we allocate exactly the right amount */ 3111 c->solve_work = 0; 3112 c->mult_work = 0; 3113 3114 c->compressedrow.use = a->compressedrow.use; 3115 c->compressedrow.nrows = a->compressedrow.nrows; 3116 if (a->compressedrow.use) { 3117 i = a->compressedrow.nrows; 3118 ierr = PetscMalloc2(i+1,&c->compressedrow.i,i+1,&c->compressedrow.rindex);CHKERRQ(ierr); 3119 ierr = PetscLogObjectMemory((PetscObject)C,(2*i+1)*sizeof(PetscInt));CHKERRQ(ierr); 3120 ierr = PetscMemcpy(c->compressedrow.i,a->compressedrow.i,(i+1)*sizeof(PetscInt));CHKERRQ(ierr); 3121 ierr = PetscMemcpy(c->compressedrow.rindex,a->compressedrow.rindex,i*sizeof(PetscInt));CHKERRQ(ierr); 3122 } else { 3123 c->compressedrow.use = PETSC_FALSE; 3124 c->compressedrow.i = NULL; 3125 c->compressedrow.rindex = NULL; 3126 } 3127 C->nonzerostate = A->nonzerostate; 3128 3129 ierr = PetscFunctionListDuplicate(((PetscObject)A)->qlist,&((PetscObject)C)->qlist);CHKERRQ(ierr); 3130 ierr = PetscMemcpy(C->ops,A->ops,sizeof(struct _MatOps));CHKERRQ(ierr); 3131 PetscFunctionReturn(0); 3132 } 3133 3134 #undef __FUNCT__ 3135 #define __FUNCT__ "MatDuplicate_SeqBAIJ" 3136 PetscErrorCode MatDuplicate_SeqBAIJ(Mat A,MatDuplicateOption cpvalues,Mat *B) 3137 { 3138 PetscErrorCode ierr; 3139 3140 PetscFunctionBegin; 3141 ierr = MatCreate(PetscObjectComm((PetscObject)A),B);CHKERRQ(ierr); 3142 ierr = MatSetSizes(*B,A->rmap->N,A->cmap->n,A->rmap->N,A->cmap->n);CHKERRQ(ierr); 3143 ierr = MatSetType(*B,MATSEQBAIJ);CHKERRQ(ierr); 3144 ierr = MatDuplicateNoCreate_SeqBAIJ(*B,A,cpvalues,PETSC_TRUE);CHKERRQ(ierr); 3145 PetscFunctionReturn(0); 3146 } 3147 3148 #undef __FUNCT__ 3149 #define __FUNCT__ "MatLoad_SeqBAIJ" 3150 PetscErrorCode MatLoad_SeqBAIJ(Mat newmat,PetscViewer viewer) 3151 { 3152 Mat_SeqBAIJ *a; 3153 PetscErrorCode ierr; 3154 PetscInt i,nz,header[4],*rowlengths=0,M,N,bs=1; 3155 PetscInt *mask,mbs,*jj,j,rowcount,nzcount,k,*browlengths,maskcount; 3156 PetscInt kmax,jcount,block,idx,point,nzcountb,extra_rows,rows,cols; 3157 PetscInt *masked,nmask,tmp,bs2,ishift; 3158 PetscMPIInt size; 3159 int fd; 3160 PetscScalar *aa; 3161 MPI_Comm comm; 3162 3163 PetscFunctionBegin; 3164 ierr = PetscObjectGetComm((PetscObject)viewer,&comm);CHKERRQ(ierr); 3165 ierr = PetscOptionsBegin(comm,NULL,"Options for loading SEQBAIJ matrix","Mat");CHKERRQ(ierr); 3166 ierr = PetscOptionsInt("-matload_block_size","Set the blocksize used to store the matrix","MatLoad",bs,&bs,NULL);CHKERRQ(ierr); 3167 ierr = PetscOptionsEnd();CHKERRQ(ierr); 3168 bs2 = bs*bs; 3169 3170 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 3171 if (size > 1) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONG,"view must have one processor"); 3172 ierr = PetscViewerBinaryGetDescriptor(viewer,&fd);CHKERRQ(ierr); 3173 ierr = PetscBinaryRead(fd,header,4,PETSC_INT);CHKERRQ(ierr); 3174 if (header[0] != MAT_FILE_CLASSID) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_FILE_UNEXPECTED,"not Mat object"); 3175 M = header[1]; N = header[2]; nz = header[3]; 3176 3177 if (header[3] < 0) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_FILE_UNEXPECTED,"Matrix stored in special format, cannot load as SeqBAIJ"); 3178 if (M != N) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"Can only do square matrices"); 3179 3180 /* 3181 This code adds extra rows to make sure the number of rows is 3182 divisible by the blocksize 3183 */ 3184 mbs = M/bs; 3185 extra_rows = bs - M + bs*(mbs); 3186 if (extra_rows == bs) extra_rows = 0; 3187 else mbs++; 3188 if (extra_rows) { 3189 ierr = PetscInfo(viewer,"Padding loaded matrix to match blocksize\n");CHKERRQ(ierr); 3190 } 3191 3192 /* Set global sizes if not already set */ 3193 if (newmat->rmap->n < 0 && newmat->rmap->N < 0 && newmat->cmap->n < 0 && newmat->cmap->N < 0) { 3194 ierr = MatSetSizes(newmat,PETSC_DECIDE,PETSC_DECIDE,M+extra_rows,N+extra_rows);CHKERRQ(ierr); 3195 } else { /* Check if the matrix global sizes are correct */ 3196 ierr = MatGetSize(newmat,&rows,&cols);CHKERRQ(ierr); 3197 if (rows < 0 && cols < 0) { /* user might provide local size instead of global size */ 3198 ierr = MatGetLocalSize(newmat,&rows,&cols);CHKERRQ(ierr); 3199 } 3200 if (M != rows || N != cols) SETERRQ4(PETSC_COMM_SELF,PETSC_ERR_FILE_UNEXPECTED,"Matrix in file of different length (%d, %d) than the input matrix (%d, %d)",M,N,rows,cols); 3201 } 3202 3203 /* read in row lengths */ 3204 ierr = PetscMalloc1((M+extra_rows),&rowlengths);CHKERRQ(ierr); 3205 ierr = PetscBinaryRead(fd,rowlengths,M,PETSC_INT);CHKERRQ(ierr); 3206 for (i=0; i<extra_rows; i++) rowlengths[M+i] = 1; 3207 3208 /* read in column indices */ 3209 ierr = PetscMalloc1((nz+extra_rows),&jj);CHKERRQ(ierr); 3210 ierr = PetscBinaryRead(fd,jj,nz,PETSC_INT);CHKERRQ(ierr); 3211 for (i=0; i<extra_rows; i++) jj[nz+i] = M+i; 3212 3213 /* loop over row lengths determining block row lengths */ 3214 ierr = PetscCalloc1(mbs,&browlengths);CHKERRQ(ierr); 3215 ierr = PetscMalloc2(mbs,&mask,mbs,&masked);CHKERRQ(ierr); 3216 ierr = PetscMemzero(mask,mbs*sizeof(PetscInt));CHKERRQ(ierr); 3217 rowcount = 0; 3218 nzcount = 0; 3219 for (i=0; i<mbs; i++) { 3220 nmask = 0; 3221 for (j=0; j<bs; j++) { 3222 kmax = rowlengths[rowcount]; 3223 for (k=0; k<kmax; k++) { 3224 tmp = jj[nzcount++]/bs; 3225 if (!mask[tmp]) {masked[nmask++] = tmp; mask[tmp] = 1;} 3226 } 3227 rowcount++; 3228 } 3229 browlengths[i] += nmask; 3230 /* zero out the mask elements we set */ 3231 for (j=0; j<nmask; j++) mask[masked[j]] = 0; 3232 } 3233 3234 /* Do preallocation */ 3235 ierr = MatSeqBAIJSetPreallocation_SeqBAIJ(newmat,bs,0,browlengths);CHKERRQ(ierr); 3236 a = (Mat_SeqBAIJ*)newmat->data; 3237 3238 /* set matrix "i" values */ 3239 a->i[0] = 0; 3240 for (i=1; i<= mbs; i++) { 3241 a->i[i] = a->i[i-1] + browlengths[i-1]; 3242 a->ilen[i-1] = browlengths[i-1]; 3243 } 3244 a->nz = 0; 3245 for (i=0; i<mbs; i++) a->nz += browlengths[i]; 3246 3247 /* read in nonzero values */ 3248 ierr = PetscMalloc1((nz+extra_rows),&aa);CHKERRQ(ierr); 3249 ierr = PetscBinaryRead(fd,aa,nz,PETSC_SCALAR);CHKERRQ(ierr); 3250 for (i=0; i<extra_rows; i++) aa[nz+i] = 1.0; 3251 3252 /* set "a" and "j" values into matrix */ 3253 nzcount = 0; jcount = 0; 3254 for (i=0; i<mbs; i++) { 3255 nzcountb = nzcount; 3256 nmask = 0; 3257 for (j=0; j<bs; j++) { 3258 kmax = rowlengths[i*bs+j]; 3259 for (k=0; k<kmax; k++) { 3260 tmp = jj[nzcount++]/bs; 3261 if (!mask[tmp]) { masked[nmask++] = tmp; mask[tmp] = 1;} 3262 } 3263 } 3264 /* sort the masked values */ 3265 ierr = PetscSortInt(nmask,masked);CHKERRQ(ierr); 3266 3267 /* set "j" values into matrix */ 3268 maskcount = 1; 3269 for (j=0; j<nmask; j++) { 3270 a->j[jcount++] = masked[j]; 3271 mask[masked[j]] = maskcount++; 3272 } 3273 /* set "a" values into matrix */ 3274 ishift = bs2*a->i[i]; 3275 for (j=0; j<bs; j++) { 3276 kmax = rowlengths[i*bs+j]; 3277 for (k=0; k<kmax; k++) { 3278 tmp = jj[nzcountb]/bs; 3279 block = mask[tmp] - 1; 3280 point = jj[nzcountb] - bs*tmp; 3281 idx = ishift + bs2*block + j + bs*point; 3282 a->a[idx] = (MatScalar)aa[nzcountb++]; 3283 } 3284 } 3285 /* zero out the mask elements we set */ 3286 for (j=0; j<nmask; j++) mask[masked[j]] = 0; 3287 } 3288 if (jcount != a->nz) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_FILE_UNEXPECTED,"Bad binary matrix"); 3289 3290 ierr = PetscFree(rowlengths);CHKERRQ(ierr); 3291 ierr = PetscFree(browlengths);CHKERRQ(ierr); 3292 ierr = PetscFree(aa);CHKERRQ(ierr); 3293 ierr = PetscFree(jj);CHKERRQ(ierr); 3294 ierr = PetscFree2(mask,masked);CHKERRQ(ierr); 3295 3296 ierr = MatAssemblyBegin(newmat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 3297 ierr = MatAssemblyEnd(newmat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 3298 PetscFunctionReturn(0); 3299 } 3300 3301 #undef __FUNCT__ 3302 #define __FUNCT__ "MatCreateSeqBAIJ" 3303 /*@C 3304 MatCreateSeqBAIJ - Creates a sparse matrix in block AIJ (block 3305 compressed row) format. For good matrix assembly performance the 3306 user should preallocate the matrix storage by setting the parameter nz 3307 (or the array nnz). By setting these parameters accurately, performance 3308 during matrix assembly can be increased by more than a factor of 50. 3309 3310 Collective on MPI_Comm 3311 3312 Input Parameters: 3313 + comm - MPI communicator, set to PETSC_COMM_SELF 3314 . bs - size of block 3315 . m - number of rows 3316 . n - number of columns 3317 . nz - number of nonzero blocks per block row (same for all rows) 3318 - nnz - array containing the number of nonzero blocks in the various block rows 3319 (possibly different for each block row) or NULL 3320 3321 Output Parameter: 3322 . A - the matrix 3323 3324 It is recommended that one use the MatCreate(), MatSetType() and/or MatSetFromOptions(), 3325 MatXXXXSetPreallocation() paradgm instead of this routine directly. 3326 [MatXXXXSetPreallocation() is, for example, MatSeqAIJSetPreallocation] 3327 3328 Options Database Keys: 3329 . -mat_no_unroll - uses code that does not unroll the loops in the 3330 block calculations (much slower) 3331 . -mat_block_size - size of the blocks to use 3332 3333 Level: intermediate 3334 3335 Notes: 3336 The number of rows and columns must be divisible by blocksize. 3337 3338 If the nnz parameter is given then the nz parameter is ignored 3339 3340 A nonzero block is any block that as 1 or more nonzeros in it 3341 3342 The block AIJ format is fully compatible with standard Fortran 77 3343 storage. That is, the stored row and column indices can begin at 3344 either one (as in Fortran) or zero. See the users' manual for details. 3345 3346 Specify the preallocated storage with either nz or nnz (not both). 3347 Set nz=PETSC_DEFAULT and nnz=NULL for PETSc to control dynamic memory 3348 allocation. See Users-Manual: ch_mat for details. 3349 matrices. 3350 3351 .seealso: MatCreate(), MatCreateSeqAIJ(), MatSetValues(), MatCreateBAIJ() 3352 @*/ 3353 PetscErrorCode MatCreateSeqBAIJ(MPI_Comm comm,PetscInt bs,PetscInt m,PetscInt n,PetscInt nz,const PetscInt nnz[],Mat *A) 3354 { 3355 PetscErrorCode ierr; 3356 3357 PetscFunctionBegin; 3358 ierr = MatCreate(comm,A);CHKERRQ(ierr); 3359 ierr = MatSetSizes(*A,m,n,m,n);CHKERRQ(ierr); 3360 ierr = MatSetType(*A,MATSEQBAIJ);CHKERRQ(ierr); 3361 ierr = MatSeqBAIJSetPreallocation_SeqBAIJ(*A,bs,nz,(PetscInt*)nnz);CHKERRQ(ierr); 3362 PetscFunctionReturn(0); 3363 } 3364 3365 #undef __FUNCT__ 3366 #define __FUNCT__ "MatSeqBAIJSetPreallocation" 3367 /*@C 3368 MatSeqBAIJSetPreallocation - Sets the block size and expected nonzeros 3369 per row in the matrix. For good matrix assembly performance the 3370 user should preallocate the matrix storage by setting the parameter nz 3371 (or the array nnz). By setting these parameters accurately, performance 3372 during matrix assembly can be increased by more than a factor of 50. 3373 3374 Collective on MPI_Comm 3375 3376 Input Parameters: 3377 + A - the matrix 3378 . bs - size of block 3379 . nz - number of block nonzeros per block row (same for all rows) 3380 - nnz - array containing the number of block nonzeros in the various block rows 3381 (possibly different for each block row) or NULL 3382 3383 Options Database Keys: 3384 . -mat_no_unroll - uses code that does not unroll the loops in the 3385 block calculations (much slower) 3386 . -mat_block_size - size of the blocks to use 3387 3388 Level: intermediate 3389 3390 Notes: 3391 If the nnz parameter is given then the nz parameter is ignored 3392 3393 You can call MatGetInfo() to get information on how effective the preallocation was; 3394 for example the fields mallocs,nz_allocated,nz_used,nz_unneeded; 3395 You can also run with the option -info and look for messages with the string 3396 malloc in them to see if additional memory allocation was needed. 3397 3398 The block AIJ format is fully compatible with standard Fortran 77 3399 storage. That is, the stored row and column indices can begin at 3400 either one (as in Fortran) or zero. See the users' manual for details. 3401 3402 Specify the preallocated storage with either nz or nnz (not both). 3403 Set nz=PETSC_DEFAULT and nnz=NULL for PETSc to control dynamic memory 3404 allocation. See Users-Manual: ch_mat for details. 3405 3406 .seealso: MatCreate(), MatCreateSeqAIJ(), MatSetValues(), MatCreateBAIJ(), MatGetInfo() 3407 @*/ 3408 PetscErrorCode MatSeqBAIJSetPreallocation(Mat B,PetscInt bs,PetscInt nz,const PetscInt nnz[]) 3409 { 3410 PetscErrorCode ierr; 3411 3412 PetscFunctionBegin; 3413 PetscValidHeaderSpecific(B,MAT_CLASSID,1); 3414 PetscValidType(B,1); 3415 PetscValidLogicalCollectiveInt(B,bs,2); 3416 ierr = PetscTryMethod(B,"MatSeqBAIJSetPreallocation_C",(Mat,PetscInt,PetscInt,const PetscInt[]),(B,bs,nz,nnz));CHKERRQ(ierr); 3417 PetscFunctionReturn(0); 3418 } 3419 3420 #undef __FUNCT__ 3421 #define __FUNCT__ "MatSeqBAIJSetPreallocationCSR" 3422 /*@C 3423 MatSeqBAIJSetPreallocationCSR - Allocates memory for a sparse sequential matrix in AIJ format 3424 (the default sequential PETSc format). 3425 3426 Collective on MPI_Comm 3427 3428 Input Parameters: 3429 + A - the matrix 3430 . i - the indices into j for the start of each local row (starts with zero) 3431 . j - the column indices for each local row (starts with zero) these must be sorted for each row 3432 - v - optional values in the matrix 3433 3434 Level: developer 3435 3436 Notes: 3437 The order of the entries in values is specified by the MatOption MAT_ROW_ORIENTED. For example, C programs 3438 may want to use the default MAT_ROW_ORIENTED=PETSC_TRUE and use an array v[nnz][bs][bs] where the second index is 3439 over rows within a block and the last index is over columns within a block row. Fortran programs will likely set 3440 MAT_ROW_ORIENTED=PETSC_FALSE and use a Fortran array v(bs,bs,nnz) in which the first index is over rows within a 3441 block column and the second index is over columns within a block. 3442 3443 .keywords: matrix, aij, compressed row, sparse 3444 3445 .seealso: MatCreate(), MatCreateSeqBAIJ(), MatSetValues(), MatSeqBAIJSetPreallocation(), MATSEQBAIJ 3446 @*/ 3447 PetscErrorCode MatSeqBAIJSetPreallocationCSR(Mat B,PetscInt bs,const PetscInt i[],const PetscInt j[], const PetscScalar v[]) 3448 { 3449 PetscErrorCode ierr; 3450 3451 PetscFunctionBegin; 3452 PetscValidHeaderSpecific(B,MAT_CLASSID,1); 3453 PetscValidType(B,1); 3454 PetscValidLogicalCollectiveInt(B,bs,2); 3455 ierr = PetscTryMethod(B,"MatSeqBAIJSetPreallocationCSR_C",(Mat,PetscInt,const PetscInt[],const PetscInt[],const PetscScalar[]),(B,bs,i,j,v));CHKERRQ(ierr); 3456 PetscFunctionReturn(0); 3457 } 3458 3459 3460 #undef __FUNCT__ 3461 #define __FUNCT__ "MatCreateSeqBAIJWithArrays" 3462 /*@ 3463 MatCreateSeqBAIJWithArrays - Creates an sequential BAIJ matrix using matrix elements provided by the user. 3464 3465 Collective on MPI_Comm 3466 3467 Input Parameters: 3468 + comm - must be an MPI communicator of size 1 3469 . bs - size of block 3470 . m - number of rows 3471 . n - number of columns 3472 . i - row indices 3473 . j - column indices 3474 - a - matrix values 3475 3476 Output Parameter: 3477 . mat - the matrix 3478 3479 Level: advanced 3480 3481 Notes: 3482 The i, j, and a arrays are not copied by this routine, the user must free these arrays 3483 once the matrix is destroyed 3484 3485 You cannot set new nonzero locations into this matrix, that will generate an error. 3486 3487 The i and j indices are 0 based 3488 3489 When block size is greater than 1 the matrix values must be stored using the BAIJ storage format (see the BAIJ code to determine this). 3490 3491 The order of the entries in values is the same as the block compressed sparse row storage format; that is, it is 3492 the same as a three dimensional array in Fortran values(bs,bs,nnz) that contains the first column of the first 3493 block, followed by the second column of the first block etc etc. That is, the blocks are contiguous in memory 3494 with column-major ordering within blocks. 3495 3496 .seealso: MatCreate(), MatCreateBAIJ(), MatCreateSeqBAIJ() 3497 3498 @*/ 3499 PetscErrorCode MatCreateSeqBAIJWithArrays(MPI_Comm comm,PetscInt bs,PetscInt m,PetscInt n,PetscInt *i,PetscInt *j,PetscScalar *a,Mat *mat) 3500 { 3501 PetscErrorCode ierr; 3502 PetscInt ii; 3503 Mat_SeqBAIJ *baij; 3504 3505 PetscFunctionBegin; 3506 if (bs != 1) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_SUP,"block size %D > 1 is not supported yet",bs); 3507 if (i[0]) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"i (row indices) must start with 0"); 3508 3509 ierr = MatCreate(comm,mat);CHKERRQ(ierr); 3510 ierr = MatSetSizes(*mat,m,n,m,n);CHKERRQ(ierr); 3511 ierr = MatSetType(*mat,MATSEQBAIJ);CHKERRQ(ierr); 3512 ierr = MatSeqBAIJSetPreallocation_SeqBAIJ(*mat,bs,MAT_SKIP_ALLOCATION,0);CHKERRQ(ierr); 3513 baij = (Mat_SeqBAIJ*)(*mat)->data; 3514 ierr = PetscMalloc2(m,&baij->imax,m,&baij->ilen);CHKERRQ(ierr); 3515 ierr = PetscLogObjectMemory((PetscObject)*mat,2*m*sizeof(PetscInt));CHKERRQ(ierr); 3516 3517 baij->i = i; 3518 baij->j = j; 3519 baij->a = a; 3520 3521 baij->singlemalloc = PETSC_FALSE; 3522 baij->nonew = -1; /*this indicates that inserting a new value in the matrix that generates a new nonzero is an error*/ 3523 baij->free_a = PETSC_FALSE; 3524 baij->free_ij = PETSC_FALSE; 3525 3526 for (ii=0; ii<m; ii++) { 3527 baij->ilen[ii] = baij->imax[ii] = i[ii+1] - i[ii]; 3528 #if defined(PETSC_USE_DEBUG) 3529 if (i[ii+1] - i[ii] < 0) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Negative row length in i (row indices) row = %d length = %d",ii,i[ii+1] - i[ii]); 3530 #endif 3531 } 3532 #if defined(PETSC_USE_DEBUG) 3533 for (ii=0; ii<baij->i[m]; ii++) { 3534 if (j[ii] < 0) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Negative column index at location = %d index = %d",ii,j[ii]); 3535 if (j[ii] > n - 1) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Column index to large at location = %d index = %d",ii,j[ii]); 3536 } 3537 #endif 3538 3539 ierr = MatAssemblyBegin(*mat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 3540 ierr = MatAssemblyEnd(*mat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 3541 PetscFunctionReturn(0); 3542 } 3543